System and method for providing scorecards to visualize services in an intelligent workload management system

ABSTRACT

The system and method described herein for providing scorecards to visualize services in an intelligent workload management system may include a computing environment having a model-driven, service-oriented architecture for creating collaborative threads to manage workloads. In particular, the management threads may converge information for describing services, applications, workloads, in an information technology infrastructure. For example, a discovery engine may reference an identity vault to capture enriched models of an infrastructure, and a management infrastructure may then generate one or more scorecards that can be used to manage the infrastructure. In particular, the scorecards may provide information for tuning or otherwise controlling risk, complexity, cost, availability, and agility versus rigidness in the infrastructure.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 61/264,562, entitled “System and Method forIntelligent Workload Management,” filed on Nov. 25, 2009, the contentsof which are hereby incorporated by reference in entirety.

In addition, this application is further related to co-pending U.S.patent application Ser. No. 12/725,241, entitled “System and Method forIntelligent Workload Management,” filed on Mar. 16, 2010, co-pendingU.S. patent application Ser. No. 12/725,263, entitled “System and Methodfor Recording Collaborative Information Technology Processes in anIntelligent Workload Management System,” filed on Mar. 16, 2010,co-pending U.S. patent application Ser. No. 12/727,837, entitled “Systemand Method for Managing Information Technology Models in an IntelligentWorkload Management System,” filed on Mar. 19, 2010, co-pending U.S.patent application Ser. No. 12/762,015, entitled “System and Method forDiscovery Enrichment in an Intelligent Workload Management System,”filed on Apr. 16, 2010, co-pending U.S. patent application Ser. No.12/900,866, entitled “System and Method for Providing Annotated ServiceLayer Blueprints in an Intelligent Workload Management System,” filed onOct. 8, 2010, and co-pending U.S. patent application Ser. No.12/645,114, entitled “System and Method for Controlling Cloud andVirtualized Data Centers in an Intelligent Workload Management System,”filed on Dec. 22, 2009, each of which further claim benefit to U.S.Provisional Patent Application Ser. No. 61/264,562, and each of whichare hereby further incorporated by reference in entirety.

FIELD OF THE INVENTION

The invention relates to a system and method for providing scorecards tovisualize services in an intelligent workload management system, and inparticular, to a computing environment having a model-driven,service-oriented architecture for creating collaborative threads tomanage workloads, wherein the management threads may convergeinformation for describing services, applications, workloads, in aninformation technology infrastructure, and further for tuning agility,risk, complexity, cost, and availability for the infrastructure,

BACKGROUND OF THE INVENTION

“Cloud computing” generally refers to a computing environment withdynamically scalable and often virtualized resources, which aretypically provided as services over the Internet. For example, cloudcomputing environments often employ the concept of virtualization as apreferred paradigm for hosting workloads on any appropriate hardware.The cloud computing model has become increasingly viable for manyenterprises for various reasons, including that the cloud infrastructuremay permit information technology resources to be treated as utilitiesthat can be automatically provisioned on demand, while also limiting thecost of services to actual resource consumption. Moreover, consumers ofresources provided in cloud computing environments can leveragetechnologies that might otherwise be unavailable. Thus, as cloudcomputing and cloud storage become more pervasive, many enterprises willfind that moving data center to cloud providers can yield economies ofscale, among other advantages.

However, while much of the information technology industry moves towardcloud computing and virtualization environments, existing systems tendto fall short in adequately addressing concerns relating to managing orcontrolling workloads and storage in such environments. For example,cloud computing environments are generally designed to support genericbusiness practices, meaning that individuals and organizations typicallylack the ability to change many aspects of the platform. Moreover,concerns regarding performance, latency, reliability, and securitypresent significant challenges, as outages and downtime can lead to lostbusiness opportunities and decreased productivity, while the genericplatform may present governance, risk, and compliance concerns. In otherwords, once organizations deploy workloads beyond the boundaries oftheir data centers, lack of visibility into the computing environmentmay result in significant management problems.

While these types of problems tend to be pervasive in cloud computingand virtualization environments due to the lack of transparency,existing systems for managing and controlling workloads that arephysically deployed and/or locally deployed in home data centers tend tosuffer from many similar problems. In particular, information technologyhas traditionally been managed in silos of automation, which are oftendisconnected from one another. For example, help desk systems typicallyinvolve a customer submitting a trouble ticket to a remedy system, witha human operator then using various tools to address the problem andclose the ticket, while monitoring systems that watch the infrastructureto remediate problems may remain isolated from the interaction betweenthe customer and the help desk despite such interaction being relevantto the monitoring system's function.

As such, because existing systems for managing infrastructure workloadsoperate within distinct silos that typically do not communicate with oneanother, context that has been exchanged between two entities can oftenbe lost when the workload moves to the next step in the chain. Whenissues surrounding workload management are considered in the context ofbusiness objectives, wherein information technology processes andbusiness issues collectively drive transitions from one silo to another,modern business tends to move at a speed that outpaces informationtechnology's ability to serve business needs. Although emerging trendsin virtualization, cloud computing, appliances, and other models fordelivering services have the potential to allow information technologyto catch up with the speed of business, many businesses lack theknowledge needed to intelligently implement these new technologies.

For example, emerging service delivery models often lead to deployedservices being composed and aggregated in new and unexpected ways. Inparticular, rather than designing and modeling systems from the groundup, new functionality is often generated on-the-fly with complexbuilding blocks that tend to include various services and applicationsthat have traditionally been isolated and stand-alone. As such, eventhough many emerging service delivery models provide administrators andusers with a wider range of information technology choices than haveever before been available, the diversity in technology often compoundsbusiness problems and increases the demand for an agile infrastructure.Thus, despite the advantages and promise that new service deliverymodels can offer businesses, existing systems tend to fall short inproviding information technology tools that can inform businesses on howto intelligently implement an information technology infrastructure in amanner that best leverage available technology to suit the particularneeds of a business.

SUMMARY OF THE INVENTION

According to one aspect of the invention, a system and method forintelligent workload management may generally provide a computingenvironment having a fluid architecture, whereby the computingenvironment may create common threads to manage workloads that convergeinformation relating to user identities and access credentials,provisioned and requested services, and physical and virtualinfrastructure resources, among other things. In one implementation,services provided in the computing environment may generally includevarious aggregated physical and/or virtual resources, while applicationsmay include various aggregated services and workloads may includevarious compositions of whole services, separate services, and/orsub-services that work together. For example, in response to a userrequesting a service that performs a particular function or application,the intelligent workload management system (or alternatively “theworkload management system”) may create a workload to manageprovisioning the user with a tuned appliance configured to perform theparticular function or application, whereby the tuned appliance mayprovide the requested service for the user. To manage the workload, theworkload management system may create a resource store that points to astorage location for the appliance, declare a service level agreementand any runtime requirements that constrain deployment for theappliance, obtain a certificate that provides attestation tokens for theuser and the appliance, and create a profile that provides an audittrail of actual lifecycle behavior for the appliance (e.g., events andperformance metrics relating to the appliance). Thus, workflows createdin the computing environment may converge various sources of informationwithin a common thread, which the workload management system may use tomanage the workload (e.g., actual metrics for a particular workload canbe compared to anticipated metrics for the workload to determine whethervarious services underlying the workload function as intended).

According to one aspect of the invention, the system and method forintelligent workload management may operate in a model-drivenarchitecture, which may merge information relating to user identitieswith services that may be running in an information technologyinfrastructure. As such, the information merged in the model-drivenarchitecture may be referenced to determine specific users ororganizational areas within the infrastructure that may be impacted inresponse to a particular change to the infrastructure model. Thus,whereas information technology has traditionally been managed withindisparate silos, where context exchanged between any two entities may belost at the next step in the chain, the model-driven architecture maytrack context for information technology workloads from start to finish.As such, tracking context for the information technology workloads mayprovide audit trails that can then be used to identify a relevant user,application, system, or other entity that can provide assistance with aparticular issue. Moreover, in the context of managing workloads forvirtualized services, where different users typically have tocommunicate with one another on-demand, the audit trail that themodel-driven architecture enables may track end-to-end workloadactivities and thereby provide visibility and notice to users,applications, systems, services, or any other suitable entity that maybe impacted by the workload.

According to one aspect of the invention, the system and method forintelligent workload management may enable agile and flexible managementfor an information technology infrastructure, which may enable theinfrastructure to move at the speed of modern business. For example, thesystem and method for intelligent workload management may furtheroperate in a service-oriented architecture unifying variousheterogeneous technologies, which may provide businesses with thecapability to deploy information technology resources in a manner thatcan meet business objectives. For example, the service-orientedarchitecture may provide adaptable, interoperable, and user-friendlyinformation technology tools to manage the infrastructure in a mannerthat addresses many typical business challenges that informationtechnology organizations face. For example, while the model-drivenarchitecture may employ virtualization features to provide manageableworkloads that can move efficiently through the infrastructure, theservice-oriented architecture may merge different technologies toprovide various coordinated systems that can cooperate to optimallyexecute portions of an overall orchestrated workload. As such, themodel-driven and service-oriented architectures may collectively derivedata from the information technology infrastructure, which may informintelligent information technology choices that meet the needs ofbusinesses and users.

According to one aspect of the invention, the system and method forintelligent workload management may be used to manage workloads createdin response to service requests. For example, any suitable user,application, system, or other entities may request a service from theworkload management system, wherein the request may include a desiredperformance level (or service level) for the service, any components orcriteria required for the service, comments to provision the service ina certain manner, or any other suitable information for the requestedservice. In response to receiving the service request, human and/orautomated approvers (or service delivery managers) may collaborativelymanage the service request and determine whether the service can beprovisioned as requested. Furthermore, the approvers may providefeedback on the service provisioning decision, which may create aninteractive collaborative “conversation” between requesters, approvers,and other entities in the management thread. In one implementation,various security policies may be built into the model to automaticallyapprove or deny certain requests, wherein the security policies may bedynamically updated in response to handling similar requests (e.g., arequest for Bit Torrent storage may be automatically denied because aparticular security policy indicates that peer-to-peer file sharingviolates a company policy).

According to one aspect of the invention, services provisioned in theworkload management system may include any suitable combination ofphysical infrastructure resources and virtualized infrastructureresources. For example, to provision virtualized services that canabstract underlying physical platforms and share computing resources ina manner that may address many needs for immediacy in businessenvironments, the workload management system may manage physicalinfrastructure resources and virtualized infrastructure resources tosupport provisioning virtualized services. Thus, the service-orientedarchitecture employed in the workload management system may enablemanagement for the physical infrastructure resources (e.g.,rack-mounting, configuring, and otherwise physically installing servers,storage resources, and other devices), and may further enable managementfor the virtualized infrastructure resources (e.g., pre-configuringprovisioned services with identity management features, denying,flagging, or auditing service requests from unauthorized entities,etc.). Moreover, the workload management system may be considered aservice in that the workload management service may be built dynamicallyin response to service requests (e.g., because a managementinfrastructure can introduce computational burdens just as any otherresource, limiting the existence of the workload managementinfrastructure to an on-demand service can free computational resourcesfor other tasks having a greater need for immediacy).

According to one aspect of the invention, to manage collaborativeservice provisioning in contexts that combine physical and virtualizedresources, the workload management system may store a history ofinteraction between requesters, approvers, and other entities in serviceprovisioning threads, and may further record, log, and save traffic andactivity between such entities in the service provisioning threads. Assuch, various processes that occur during service provisioning may berecorded and injected into a real-time stream that can subsequently beplayed back, thereby capturing the service provisioning processes as awhole, including any responses that human and/or automated entities mayprovide during the collaborative process. During processes forcollaboratively managing the information technology infrastructure, theworkload management system may expose portions of the infrastructuremodel to entities involved in the management processes. In oneimplementation, the workload management system may expose “just enoughcontext” to entities involved in the management processes, whereby theinvolved entities may view the respective portions of the infrastructuremodel for which such entities have management responsibility (e.g.,prior to implementing any particular change to the infrastructure, theworkload management system may query the model and determine an impactof the change, notify impacted entities, etc.).

According to one aspect of the invention, virtualized servicesprovisioned in the workload management system may further includeinjection points for adding and/or removing information from theprovisioned services. For example, any particular virtualized servicemay generally include a layered architecture that includes injectionpoints for inserting “zero residue” management agents that can managethe service and ensure that the service functions correctly. Thus, inone implementation, zero residue management agents may be insertedwithin virtualized services at build time, run time, or any othersuitable point in a lifecycle for the virtualized services, wherein theparticular management agents inserted within the virtualized servicesmay depend on a type of management required. For example, the workloadmanagement system may analyze a configuration of the service, alifecycle point for the service, or other suitable information for theservice to derive a recipe of the management agents to be injected(e.g., the recipe may depend on a required service level for theservice, a current operational state for the infrastructure model,services running in the infrastructure, a type of management requiredfor the running services, etc.).

Other objects and advantages of the invention will be apparent to thoseskilled in the art based on the following drawings and detaileddescription.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a block diagram of an exemplary model-drivenarchitecture in a system for intelligent workload management, accordingto one aspect of the invention.

FIG. 1B illustrates a block diagram of an exemplary service-orientedarchitecture in the system for intelligent workload management,according to one aspect of the invention.

FIG. 2 illustrates a flow diagram of an exemplary method for intelligentworkload management, according to one aspect of the invention.

FIG. 3 illustrates a block diagram of an exemplary system fordiscovering enriched information technology models in the intelligentworkload management system, according to one aspect of the invention.

FIG. 4 illustrates a flow diagram of an exemplary method for generatingscorecards to visualize and tune services in the intelligent workloadmanagement system, according to one aspect of the invention.

FIG. 5A illustrates an exemplary service listing scorecard that can beused to visualize and tune services in the intelligent workloadmanagement system, according to one aspect of the invention.

FIG. 5B illustrates an exemplary operation index scorecard that can beused to visualize and tune an infrastructure operational state in theintelligent workload management system, according to one aspect of theinvention.

FIG. 5C illustrates an exemplary risk heat map scorecard that can beused to visualize and tune risk to coverage ratios in the intelligentworkload management system, according to one aspect of the invention.

FIG. 5D illustrates an exemplary service placement scorecard that can beused to visualize and tune service placements in the intelligentworkload management system, according to one aspect of the invention.

FIG. 6 illustrates a flow diagram of an exemplary method for tuning aninfrastructure with the service scorecards in the intelligent workloadmanagement system, according to one aspect of the invention.

DETAILED DESCRIPTION

According to one aspect of the invention, FIG. 1A illustrates anexemplary model-driven architecture 100A in a system for intelligentworkload management, while FIG. 1B illustrates an exemplaryservice-oriented architecture 100B in the system for intelligentworkload management. In one implementation, the model-drivenarchitecture 100A shown in FIG. 1A and the service-oriented architecture100B shown in FIG. 1B may include various components that operate in asubstantially similar manner to provide the functionality that will bedescribed in further detail herein. Thus, any description providedherein for components having identical reference numerals in FIGS. 1Aand 1B will be understood as corresponding to such components in bothFIGS. 1A and 1B, whether or not explicitly described.

In one implementation, the model-driven architecture 100A illustrated inFIG. 1A and the service-oriented architecture 100B illustrated in FIG.1B may provide an agile, responsive, reliable, and interoperableinformation technology environment, which may address various problemsassociated with managing an information technology infrastructure 110(e.g., growing revenues and cutting costs, managing governance, risk,and compliance, reducing times to innovate and deliver products tomarkets, enforcing security and access controls, managing heterogeneoustechnologies and information flows, etc.). To that end, the model-drivenarchitecture 100A and the service-oriented architecture 100B may providea coordinated design for the intelligent workload management system (oralternatively “the workload management system”), wherein the coordinateddesign may integrate technologies for managing identities, enforcingpolicies, assuring compliance, managing computing and storageenvironments, providing orchestrated virtualization, enablingcollaboration, and providing architectural agility, among other things.The model-driven architecture 100A and the service-oriented architecture100B may therefore provide a flexible framework that may enable theworkload management system to allocate various resources 114 in theinformation technology infrastructure 110 in a manner that balancesgovernance, risk, and compliance with capacities for internal andexternal resources 114. For example, as will be described in furtherdetail herein, the workload management system may operate within theflexible framework that the model-driven architecture 100A and theservice-oriented architecture 100B to deliver information technologytools for managing security, performance, availability, and policyobjectives for services provisioned in the information technologyinfrastructure 110.

Identity Management

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may enable managing identities in the information technologyinfrastructure 110. In particular, managing identities may present animportant concern in the context of managing services in the informationtechnology infrastructure 110 because security, performance,availability, policy objectives, and other variables may have differentimportance for different users, customers, applications, systems, orother resources 114 that operate in the information technologyinfrastructure 110. As such, the model-driven architecture 100A and theservice-oriented architecture 100B may include various components thatenable identity management in the information technology infrastructure110.

For example, in one implementation, the workload management system mayinclude an access manager 120 (e.g., Novell Access Manager), which maycommunicate with an identity vault 125 and control access to content,applications, services, and other resources 114 in the informationtechnology infrastructure 110. In one implementation, the access manager120 may enforce various policy declarations to provide authenticationservices for any suitable component in the information technologyinfrastructure 110. For example, the identity vault 125 may includevarious directories that organize user accounts, roles, policies, andother identity information that the access manager 120 can reference togenerate authorization decisions. The access manager 120 and theidentity vault 125 may further support federated user identities,wherein a user at any particular client resource 115 may submit singlesign-on authentication credentials to the access manager 120, which maythen control access to any suitable resource 114 in the informationtechnology infrastructure 110 with the single sign-on authenticationcredentials (e.g., user names, identifiers, passwords, smart cards,biometrics, etc.). Moreover, the identity information stored in theidentity vault 125 may be provided to a synchronization engine 150,whereby the synchronization engine 150 may provide interoperable andtransportable identity information throughout the architecture (e.g.,via an identity fabric within an event bus 140 that manages transportthroughout the architecture).

In one implementation, providing the identity information stored in theidentity vault 125 to the synchronization engine 150 may form portableidentities that correspond to independent digital representations forvarious users, applications, systems, or other entities that interactwith the information technology infrastructure 110. In particular, theidentities maintained in the synchronization engine 150 may generallyinclude abstractions that can provide access to authoritativeattributes, active roles, and valid policies for entities that theidentity abstractions represent. Thus, synchronizing the identityinformation stored in the identity vault 125 with the synchronizationengine 150 may provide independent and scalable digital identities thatcan be transported across heterogeneous applications, services,networks, or other systems, whereby the workload management system mayhandle and validate the digital identities in a cooperative,interoperable, and federated manner.

In one implementation, the identities stored in the identity vault 125and synchronized with the synchronization engine 150 may be customizedto define particular attributes and roles that the identities mayexpose. For example, a user may choose to create one identity thatexposes every attribute and role for the user to applications, services,or other systems that reside within organizational boundaries, anotheridentity that limits the attributes and roles exposed to certain serviceproviders outside the organizational boundaries, and another identitythat provides complete anonymity in certain contexts. The identitiesmaintained in the synchronization engine 150 may therefore provideawareness over any authentication criteria that may be required toenable communication and collaboration between entities that interactwith the workload management system. For example, the synchronizationengine 150 may include a service that can enforce policies controllingwhether certain information stored in the identity vault 125 can beshared (e.g., through the access manager 120 or other informationtechnology tools that can manage and customize identities).

In one implementation, the workload management system may further manageidentities in a manner that enables infrastructure workloads to functionacross organizational boundaries, wherein identities for various users,applications, services, and other resources 114 involved ininfrastructure workloads may be managed with role aggregation policiesand logic that can support federated authentication, authorization, andattribute services. For example, in one implementation, the accessmanager 120, the identity vault 125, and the synchronization engine 150may manage identity services externally to applications, services, andother resources 114 that consume the identities, which may enable theworkload management system to control access to services for multipleapplications using consistent identity interfaces. In particular, theaccess manager 120, the identity vault 125, and the synchronizationengine 150 may define standard interfaces for managing the identityservices, which may include authentication services, push authorizationservices (e.g., tokens, claims, assertions, etc.), pull authorizationservices (e.g., requests, queries, etc.), push attribute services (e.g.,updates), pull attribute services (e.g., queries), and audit services.

As such, in one implementation, the workload management system mayemploy the identity services provided in the model-driven architecture100A and the service-oriented architecture 100B to apply policies forrepresenting and controlling roles for multiple identities within anyparticular session that occurs in the information technologyinfrastructure 110. For example, in response to a session that includesa user logging into a client machine 115 and invoking a backup service,the workload management system may manage the session with multipleidentities that encompass the user, the backup service, and the clientmachine 115. The workload management system may further determine thatthe identity for the client machine 115 represents an unsecured machinethat resides outside an organizational firewall, which may result in theworkload management system retrieving a policy from the identity vault125 and/or the synchronization engine 150 and applying the policy to thesession (e.g., the policy may dynamically prevent the machine 115 andthe user from being active in the same session). Thus, the workloadmanagement system may manage multiple identities that may be involved inany particular service request to control and secure access toapplications, services, and other resources 114 in the informationtechnology infrastructure 110.

In one implementation, the model-driven architecture 100A and theservice-oriented architecture 100B may further provide identity servicesfor delegating rights in delegation chains that may involve variousdifferent levels of identities. In particular, any particular user mayhave various roles, attributes, or other identities that define variousrights for the user. As such, in one implementation, the rightsdelegation identity service may enable the user to delegate atime-bounded subset of such rights to a particular service, wherein theservice can then make requests to other services on behalf of the userduring the delegated time. For example, a user may delegate rights to abackup service that permits the backup service to read a portion of aclustered file system 195 during a particular time interval (e.g., 2a.m. to 3 a.m.). In response to the file system 195 receiving the readrequest from the backup service, the identity services may enable thefile system 195 to audit identities for the backup service and the user,and further to constrain read permissions within the file system 195based on the relevant rights defined by the identities for the backupservice for the user.

In one implementation, the model-driven architecture 100A and theservice-oriented architecture 100B may further provide identity servicesfor defining relative roles, wherein relative roles may be defined wherea principal user, application, service, or other entity can only assumea particular role for a particular action when a target of the actionhas a particular set of identities. For example, a user having a doctorrole may only assume a doctor-of-record relative role if an identity fora target of the doctor-of-record action refers to one of the user'spatients. In another example, applications may request controlled accessto information about an identity for a certain user, wherein theapplication may retrieve the requested information directly from theaccess-controlled identity for the user. In particular, the workloadmanagement system may determine the information requested by theapplication and create a workload that indicates to the user theinformation requested by the application and any action that theapplication may initiate with the requested information. The user maythen make an informed choice about whether to grant the applicationaccess to the requested information. Thus, having identities to enableapplications may eliminate a need for application-specific data storageor having the application access separate a directory service or anotheridentity information source.

Thus, in the model-driven architecture 100A and the service-orientedarchitecture 100B, the identity management services may create craftedidentities combined from various different types of identity informationfor various users, applications, services, systems, or other informationtechnology resources 114. In one implementation, while the identityinformation may generally be stored and maintained in the identity vault125, the identity information can be composed and transformed throughthe access manager 120 and/or the synchronization engine 150, with theresulting identity information providing authoritative statements forrepresented entities that span multiple authentication domains withinand/or beyond boundaries for the information technology infrastructure110. For example, an identity for a user may be encapsulated within atoken that masks any underlying credential authentication, identityfederation, and attribute attestation. Moreover, in one implementation,the identity services may further support identities that outliveentities that the identities represent and multiple identity subsetswithin a particular identity domain or across multiple identity domains.As such, the identity services provided in the model-driven architecture100A and the service-oriented architecture 100B may include variousforms of authentication, identifier mapping, token transformation,identity attribute management, and identity relationship mapping.

Policy Enforcement

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may enable enforcing policies in the information technologyinfrastructure 110. In particular, enforcing policies may present animportant concern in the context of managing services in the informationtechnology infrastructure 110 because policies may be driven frommultiple hierarchies and depend on operational, legislative, andorganizational requirements that can overlap, contradict, and/oroverride each other. As such, the model-driven architecture 100A and theservice-oriented architecture 100B may include various components fordefining policies in standardized languages that can be translated,merged, split, or otherwise unified as needed. To that end, the workloadmanagement system may have multiple policy decision points and policydefinition services for consistently managing and enforcing policies inthe information technology infrastructure 110

As such, in one implementation, the model-driven architecture 100A andthe service-oriented architecture 100B may provide standard policylanguages and service interfaces that enable the workload managementsystem to make consistent decisions based on flexible user needs. Inparticular, any suitable resource 114 (including workloads andcomputational infrastructure) may be provided with access tostandardized instrumentation that provides knowledge regardinginformation that may be available, desired, or allowed in the workloadmanagement system. In one implementation, the workload management systemmay invoke various cooperating policy services to determine suitablephysical resources 114 a (e.g., physical servers, hardware devices,etc.), virtualized resources 114 b (e.g., virtual machine images,virtualized servers, etc.), configuration resources 114 c (e.g.,management agents, translation services, etc.), storage resources (e.g.,the clustered file system 195, one or more databases 155, etc.), orother resources 114 for a particular workload. For example, thesynchronization engine 150 may dynamically retrieve various policiesstored in the databases 155, and an event audit service 135 b may thenevaluate the policies maintained in the synchronization engine 150independently from services that subsequently enforce policy decisions(e.g., the event audit service 135 b may determine whether the policiespermit access to certain information for a particular application andthe application may then enforce the policy determination).

In one implementation, separating policy evaluation within the eventaudit service 135 b from policy enforcement within consuming servicesmay enable the workload management system to access the consumingservices and manage policy-based control for the service in anindependent and simultaneous manner. The event audit service 135 b mayinclude a standardized policy definition service that can be used todefine policies that span multiple separate application and managementdomains. For example, in one implementation, the policy definitionservice may create, manage, translate, and/or process policiesseparately from other service administration domains and interfaces. Assuch, the policy definition service may provide interoperability for theseparate domains and interfaces, and may further enable complianceservices that may be provided in a correlation system 165 andremediation services that may be provided in a workload service 135 a.

In one implementation, to ensure correct and effective policy decisions,the policy definition service provided within the event audit service135 b may be configured to obtain data relating to a current state andconfiguration for resources 114 managed in the infrastructure 110 inaddition to data relating to dependencies or other interactions betweenthe managed resources 114. For example, a management infrastructure 170may include a discovery engine 180 b that dynamically monitors variousevents that the infrastructure 110 generates and pushes onto the eventbus 140, which may include an event backplane for transporting theevents. Moreover, the discovery engine 180 b may query theinfrastructure 110 to determine relationships and dependencies amongusers, applications, services, and other resources 114 in theinfrastructure 110. As such, the discovery engine 180 b may monitor theevent bus 140 to obtain the events generated in the infrastructure 110and synchronize the events to the synchronization engine 150, and mayfurther synchronize information relating to the relationships anddependencies identified in the infrastructure 110 to the synchronizationengine 150. In one implementation, the event audit service 135 b maythen evaluate any events, resource relationships, resource dependencies,or other information describing the operational state and theconfiguration state of the infrastructure 110 in view of any relevantpolicies and subsequently provide any such policy evaluations torequesting entities.

In one implementation, the policy definition service may includestandard interfaces for defining policies in terms of requirements,controls, and rules. For example, the requirements may generally beexpressed in natural language in order to describe permittedfunctionality, prohibited functionality, desirable functionality, andundesirable functionality, among other things (e.g., the event auditservice 135 b may capture legislative regulations, business objectives,best practices, or other policy-based requirements expressed in naturallanguage). The controls may generally associate the requirements toparticular objects that may be managed in the workload managementsystem, such as individual users, groups of users, physical resources114 a, virtualized resources 114 b, or any other suitable object orresource 114 in the infrastructure 110. In one implementation, thepolicy definition service may further define types for the controls. Forexample, the type may include an authorization type that associates anidentity with a particular resource 114 and action (e.g., for certainidentities, authorizing or denying access to a system or a file,permission to alter or deploy a policy, etc.), or the type may includean obligation type that mandates a particular action for an identity.

Thus, in one implementation, translating requirements into controls maypartition the requirements into multiple controls that may definepolicies for a particular group of objects. Furthermore, rules may applycertain controls to particular resources 114, wherein rules mayrepresent concrete policy definitions. For example, the rules may betranslated directly into a machine-readable and machine-executableformat that information technology staff may handle and that the eventaudit service 135 b may evaluate in order to manage policies. In oneimplementation, the rules may be captured and expressed in any suitabledomain specific language, wherein the domain specific language mayprovide a consistent addressing scheme and data model to instrumentpolicies across multiple domains. For example, a definitive softwarelibrary 190 may include one or more standardized policy libraries fortranslating between potentially disparate policy implementations, whichmay enable the event audit service 135 b to provide federated policiesinteroperable across multiple different domains. As such, the rules thatrepresent the policy definitions may include identifiers for anoriginating policy implementation, which the policy definition servicemay then map to the controls that the rules enforce and to the domainspecific policy language used in the workload management system (e.g.,through the definitive software library 190).

Compliance Assurance

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may enable monitoring for compliance assurances in the informationtechnology infrastructure 110. In particular, compliance assurance maypresent an important concern in the context of managing services in theinformation technology infrastructure 110 because policy enforcementencompasses issues beyond location, access rights, or other contextualinformation within the infrastructure (e.g., due to increasing mobilityin computing environments). As such, the model-driven architecture 100Aand the service-oriented architecture 100B may define metadata thatbounds data to characteristics of data. To that end, the workloadmanagement system may employ a standard metadata format to provideinteroperability between policies from multiple organizations to enablethe policies to cooperate with one another and provide policy-basedservice control. For example, certain infrastructure workloads mayexecute under multiple constraints defined by users, the infrastructure110, sponsoring organizations, or other entities, wherein complianceassurance may provide users with certification that the workloads wereproperly assigned and executed according to the constraints. In anotherexample, sponsoring organizations and governing bodies may definecontrol policies that constrain workloads, wherein compliance assurancein this context may include ensuring that only authorized workloads havebeen executed against approved resources 114.

As such, in one implementation, the model-driven architecture 100A andthe service-oriented architecture 100B may provide preventativecompliance assurance through a compliance management service thatsupports remediation in addition to monitoring and reporting. Forexample, when workloads move from data centers internal to theinfrastructure 110 into third party processing centers, cloud computingenvironments, or other environments having reusable computing resourcepools where services can be relocated, the workload management systemmay generate compliance reports 145 that indicate whether anyconstraints defined for the workloads have been satisfied (e.g., thatauthorized entities perform the correct work in the correct manner, asdefined within the workloads). Thus, compliance may generally be definedto include measuring and reporting on whether certain policieseffectively ensure confidentiality and availability for informationwithin workloads, wherein the resulting compliance reports 145 maydescribe an entire process flow that encompasses policy definition,relationships between configurations and activities that do or do notcomply with the defined policies, and identities of users, applications,services, systems, or other resources 114 involved in the process flow.

In one implementation, the workload management system may provide thecompliance management service for workloads having specificationsdefined by users, and further for workloads having specificationsdefined by organizations. For example, users may generally definevarious specifications to identify operational constraints and desiredoutcomes for workloads that the users create, wherein the compliancemanagement service may certify to the users whether or not theoperational constraints and desired outcomes have been correctlyimplemented. With respect to organizational workloads, organizations maydefine various specifications identifying operational constraints anddesired outcomes for ensuring that workloads comply with governmentalregulations, corporate best practices, contracts, laws, and internalcodes of conduct. Thus, the compliance management service may integratethe identity management services and the policy definition servicedescribed above to provide the workload management system with controlover configurations, compliance event coverage, and remediation servicesin the information technology infrastructure 110.

In one implementation, the compliance management service may operatewithin a workload engine 180 a provided within the managementinfrastructure 170 and/or a workload service 135 b in communication withthe synchronization engine 150. The workload engine 180 a and/or theworkload service 135 b may therefore execute the compliance managementservice to measure and report on whether workloads comply with relevantpolicies, and further to remediate any non-compliant workloads. Forexample, the compliance management service may use the integratedidentity management services to measure and report on users,applications, services, systems, or other resources 114 that may beperforming operational activity that occurs in the informationtechnology infrastructure 110. In particular, the compliance managementservice may interact with the access manager 120, the identity vault125, the synchronization engine 150, or any other suitable source thatprovides federated identity information to retrieve identities for theentities performing the operational activity, validate the identities,determine relationships between the identities, and otherwise map theidentities to the operational activity. For example, in oneimplementation, the correlation system 165 may provide analytic servicesto process audit trails for any suitable resource 114 (e.g., correlatingthe audit trails and then mapping certain activities to identities forresources 114 involved in the activities). Furthermore, in response tothe correlation system 165 processing the audit trails and determiningthat certain policies have been violated, the correlation system 165 mayinvoke one or more automated remediation workloads to initiateappropriate action for addressing the policy violations.

In one implementation, the compliance management service may further usethe integrated policy definition service to monitor and report on theoperational activity that occurs in the information technologyinfrastructure 110 and any policy evaluation determinations that theevent audit service 135 b generates through the policy definitionservice. For example, in one implementation, the workload engine 180 aand/or the workload service 135 b may retrieve information from aconfiguration management database 185 a or other databases 155 thatprovide federated configuration information for managing the resources114 in the information technology infrastructure 110. The workloadengine 180 a and/or the workload service 135 b may therefore execute thecompliance management service to perform scheduled and multi-stepcompliance processing, wherein the compliance processing may includecorrelating operational activities with identities and evaluatingpolicies that may span various different policy domains in order togovern the information technology infrastructure 110. To that end, themodel-driven architecture 100A and the service-oriented architecture1008 may provide various compliance management models may be used in thecompliance management service.

In one implementation, the compliance management models may include awrapped compliance management model that manages resources 114 lackinginternal awareness over policy-based controls. The compliance managementservice may augment the resources 114 managed in the wrapped compliancemodel with one or more policy decision points and/or policy enforcementpoints that reside externally to the managed resources 114 (e.g., theevent audit service 135 b). For example, the policy decision pointsand/or the policy enforcement points may intercept any requests directedto the resources 114 managed in the wrapped compliance model, generatepolicy decisions that indicate whether the resources 114 can properlyperform the requests, and then enforce the policy decisions (e.g.,forwarding the requests to the resources 114 in response to determiningthat the resources 114 can properly perform the requests, denying therequests in response to determining that the resources 114 can properlyperform the requests, etc.). Thus, because the resources 114 managed inthe wrapped compliance model generally perform any requests that theresources 114 receive without considering policy-based controls orcompliance issues, the event audit service 135 b may further execute thecompliance management service to wrap, coordinate, and synthesize anaudit trail that includes data obtained from the managed resources 114and the wrapping policy definition service.

In one implementation, the compliance management models may include adelegated compliance management model to manage resources 114 thatimplement a policy enforcement point and reference an external policydecision point, wherein the resources 114 managed in the delegatedcompliance management model may have limited internal awareness overpolicy-based controls. As such, in one implementation, the compliancemanagement service may interleave policy decisions or other controloperations generated by the external policy decision point with theinternally implemented policy enforcement point to provide complianceassurance for the resources 114 managed in the delegated compliancemanagement model. The delegated compliance management model maytherefore represent a hybrid compliance model, which may apply to anysuitable service that simultaneously anticipates complianceinstrumentation but lacks internal policy control abstractions (e.g.,the internally implemented policy enforcement point may anticipate thecompliance instrumentation, while the externally referenced policydecision point has the relevant policy control abstractions). Thus, inthe delegated compliance management model, the compliance managementservice may have fewer objects to coordinate than in the wrappedcompliance management model, but the event audit service 135 b maynonetheless execute the compliance management service to coordinate andsynthesize an audit trail that includes data obtained from the managedresources 114 and the delegated external policy decision point.

In one implementation, the compliance management models may include anembedded compliance management model that manages resources 114 thatinternally implement policy enforcement points and policy decisionpoints, wherein the resources 114 managed in the embedded compliancemanagement model may have full internal awareness over policy-basedcontrols. As such, in one implementation, the resources 114 managed inthe embedded compliance management model may employ the internallyimplemented policy enforcement points and policy decision points toinstrument any service and control operations for requests directed tothe resources 114. In one implementation, to provide flexible complianceassurance, resources 114 managed in the embedded compliance managementmodel may expose configuration or customization options via anexternalized policy administration point. Thus, the embedded compliancemanagement model may provide an integrated and effective audit trail forcompliance assurance, which may often leave the compliance managementservice free to perform other compliance assurance processes.

Accordingly, in one implementation, the compliance management servicemay obtain information for any resource 114 managed in the informationtechnology infrastructure 110 from the configuration management database185 a or other databases 155 that include a federated namespace for themanaged resources 114, configurations for the managed resources 114, andrelationships among the managed resources 114. In addition, thecompliance management service may reference the configuration managementdatabase 185 a or other the databases 155 to arbitrate configurationmanagement in the infrastructure 110 and record previous configurationshistories for the resources 114 in the configuration management database185 a or other databases 155. As such, the compliance management servicemay generally maintain information relating to identities,configurations, and relationships for the managed resources 114, whichmay provide a comparison context for analyzing subsequent requests tochange the infrastructure 110 and identifying information technologyservices that the requested changes may impact.

Computing and Storage Environments

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may include managing computing and storage environments thatsupport services in the infrastructure 110. In particular, in oneimplementation, the computing and storage environments used to supportservices in the infrastructure 110 may employ Linux operatingenvironments, which may generally include an operating systemdistribution with a Linux kernel and various open source packages (e.g.,gcc, glibc, etc.) that collectively provide the Linux operatingenvironments. In one implementation, the Linux operating environmentsmay generally provide a partitioned distribution model for managing thecomputing and storage environments employed in the workload managementsystem. Further, in one implementation, a particular Linux distributionmay be bundled for operating environments pre-installed in the workloadmanagement system (e.g., openSUSE, SUSE Linux Enterprise, etc.), whichmay enable vendors of physical hardware resources 114 a to support everyoperating system that the vendors' customers employ without overheadthat may introduced with multiple pre-installed operating environmentchoices.

In one implementation, the partitioned distribution model may partitionthe Linux operating environments into a physical hardware distribution(often referred to as a “pDistro”), which may include physical resources114 a that run over hardware to provide a physical hosting environmentfor virtual machines 114 b. For example, in one implementation, thephysical hardware distribution may include the Linux kernel and varioushypervisor technologies that can run the virtual machines 114 b over theunderlying physical hosting environment, wherein the physical hardwaredistribution may be certified for existing and future-developed hardwareenvironments to enable the workload management system to support futureadvances in the Linux kernel and/or hypervisor technologies.Alternatively (or additionally), the workload management system mayrelease the physical hardware distribution in a full Linux distributionversion to provide users with the ability to take advantage of futureadvances in technologies at a faster release cycle.

In one implementation, the partitioned distribution model may furtherpartition the Linux operating environments into a virtual softwaredistribution (often referred to as a “vDistro”), which may includevirtual machines 114 b deployed for specific applications or servicesthat run, enable, and otherwise support workloads. More particularly,any particular virtual software distribution may generally include oneor more Linux package or pattern deployments, whereby the virtualmachines 114 b may include virtual machines images with “just enoughoperating system” (JeOS) to support the package or pattern deploymentsneeded to run the applications or services for the workloads. In oneimplementation, the virtual software distribution may include aparticular Linux product (e.g., SUSE Linux Enterprise Server) bundledwith hardware agnostic virtual drivers, which may provide configurationresources 114 c for tuning virtualized resources 114 b for optimizedperformance.

In one implementation, the particular virtual software distribution maybe certified for governmental security requirements and for certainapplication vendors, which may enable the workload management system toupdate any physical resources 114 a in the physical hardwaredistribution underlying the virtual software distribution withoutcompromising support contracts with such vendors. In particular, inresponse to future changes in technology that may improve support forLinux operating environments, resulting improvements may occur intechniques for building and deploying Linux operating environments.Thus, where many application vendors currently tend to only providesupport for certain Linux applications that run in certain Linuxversions, the workload management system may enable support for anyparticular Linux application or version, which may drive Linuxintegration and adoption across the information technologyinfrastructure 110. In one implementation, for example, the workloadmanagement system may employ Linux applications and distributionscreated using a build system that enables any suitable application to bebuilt and tested on different versions of Linux distributions (e.g., anopenSUSE Build Service, SUSE Studio, etc.). For example, in response toreceiving a request that includes unique specifications for a particularLinux application, the workload management system may notifydistribution developers to include such specifications in theapplication, with the specifications then being made available to otherapplication developers.

Thus, in one implementation, the Linux build system employed in theworkload management system may enable distribution engineers anddevelopers to detect whether changes to subsequent application releasesconflict with or otherwise break existing applications. In particular,changes in systems, compiler versions, dependent libraries, or otherresources 114 may cause errors in the subsequent application releases,wherein commonly employing the Linux build system throughout theworkload management system may provide standardized application support.For example, in one implementation, the workload management system mayemploy certified implementations of the Linux Standard Base (LSB), whichmay enable independent software vendors (ISVs) to verify compliance, andmay further provide various support services that can providepolicy-based automated remediation for the Linux operating environmentsthrough the LSB Open Cluster Framework (OCF).

In one implementation, the Linux operating environments in the workloadmanagement system may provide engines that support orchestratedvirtualization, collaboration, and architectural agility, as will bedescribed in greater detail below. Further, to manage identities,enforce policies, and assure compliance, the Linux operatingenvironments may include a “syslog” infrastructure that coordinate andmanages various internal auditing requirements, while the workloadmanagement system may further provide an audit agent to augment theinternal auditing capabilities that the “syslog” infrastructure provides(e.g., the audit agent may operate within the event audit service 135 bto uniformly manage the Linux kernel, the identity services, the policyservices, and the compliance services across the workload managementsystem). For example, in one implementation, partitioning the monolithicLinux distribution within a multiple layer model that includes physicalhardware distributions and virtual software distributions may enableeach layer of the operating system to be developed, delivered, andsupported at different schedules. In one implementation, a schedulingsystem 180 c may coordinate such development, delivery, and support in amanner that permits dynamic changes to the physical resources 114 a inthe infrastructure 110, which provide stability and predictability forthe infrastructure 110.

In one implementation, partitioning the Linux operating environmentsinto physical hardware distributions and virtual software distributionsmay further enable the workload management system to run workloads incomputing and storage environments that may not necessarily beco-located or directly connected to physical storage systems thatcontain persistent data. For example, the workload management system maysupport various interoperable and standardized protocols that providecommunication channels between users, applications, services, and ascalable replicated storage system, such as the clustered file system195 illustrated in FIG. 1A, wherein such protocols may provideauthorized access between various components at any suitable layerwithin the storage system.

In one implementation, the clustered file system 195 may generallyinclude various block storage devices, each of which may host variousdifferent file systems. In one implementation, the workload managementsystem may provide various storage replication and version managementservices for the clustered file system 195, wherein the various blockstorage devices in the clustered file system 195 may be organized in ahierarchical stack, which may enable the workload management system toseparate the clustered file system 195 from operating systems andcollaborative workloads. As such, the storage replication and versionmanagement services may enable applications and storage services to runin cloud computing environments located remotely from client resources115.

In one implementation, various access protocols may providecommunication channels that enable secure physical and logicaldistributions between subsystem layers in the clustered file system 195(e.g., a Coherent Remote File System protocol, a Dynamic StorageTechnology protocol, which may provide a file system-to-file systemprotocol that can place a particular file in one of various differentfile systems based on various policies, or other suitable protocols).Furthermore, traditional protocols for access files from a clientresource 115 (e.g., HTTP, NCP, AFP, NFS, etc.) may be written to filesystem specific interfaces defined in the definitive software library190. As such, the definitive software library 190 may provide mappingsbetween authorization and semantic models associated with the accessprotocols and similar elements of the clustered file system 195, whereinthe mappings may be dynamically modified to handle any new protocolsthat support cross-device replication, device snapshots, block-levelduplication, data transfer, and/or services for managing identities,policies, and compliance.

As such, the storage replication and version management services mayenable users to create workloads that define identity and policy-basedstorage requirements, wherein team members identities may be used todynamically modify the team members and any access rights defined forthe team members (e.g., new team members may be added to a “writeaccess” group, users that leave the team may be moved to a “read access”group or removed from the group, policies that enforce higher compliancelevels for Sarbanes-Oxley may be added in response to an executive userjoining the team, etc.). For example, a user that heads a distributedcross-department team developing a new product may define variousmembers for the team and request permission for self-defined accesslevels for the team members (e.g., to enable the team members toindividually specify a storage amount, redundancy level, and bandwidthto allocate). The workload management system may then provide finegrained access control for a dynamic local storage cache, which may movedata stored in the in the clustered file system 195 to a local storagefor a client resource 115 that accesses the data (i.e., causing the datato appear local despite being persistently managed in the clustered filesystem 195 remotely from the client resource 115). As such, individualusers may then use information technology tools define for local areanetworks to access and update the data, wherein the replication andversion management services may further enable the individual users tocapture consistent snapshots that include a state of the data acrossvarious e-mail systems, databases 155, file systems 195, cloud storageenvironments, or other storage devices.

In one implementation, the storage replication and version managementservices may further enable active data migration and auditing formigrated data. For example, policies or compliance issues may requiredata to be maintained for a longer lifecycle than hardware and storagesystems, wherein the workload management system may actively migratecertain data to long-term hardware or an immutable vault in theclustered file system 195 to address such policies or compliance issues.Furthermore, identity-based management for the data stored in theclustered file system 195 may enable the workload management system tocontrol, track, and otherwise audit ownership and access to the data,and the workload management system may further classify and tag the datastored in the clustered file system 195 to manage the data storedtherein (e.g., the data may be classified and tagged to segregateshort-term data from long-term data, maintain frequently used data onfaster storage systems, provide a content-addressed mechanism forefficiently searching potentially large amounts of data, etc.). Thus,the workload management system may use the storage replication andversion management services to generate detailed reports 145 for thedata managed in the clustered file system.

In one implementation, the storage replication and version managementservices may further provide replication services at a file level, whichmay enable the workload management system to control a location, anidentity, and a replication technique (e.g., block-level versusbyte-level) for each file in the clustered file system 195. In addition,the storage replication and version management services may furtherenable the workload management system to manage storage costs and energyconsumption (e.g., by controlling a number of copies created for anyparticular file, a storage medium used to store such copies, a storagelocation used to store such copies, etc.). Thus, integrating federatedidentities managed in the identity vault 125 with federated policydefinition services may enable the workload management system to managethe clustered file system 195 without synchronizing or otherwise copyingevery identity with separate identity stores associated with differentstorage subsystems.

Orchestrated Virtualization

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may provide orchestrated virtualization for managing servicesprovided in the information technology infrastructure 110. Inparticular, virtualization generally ensures that a machine runs atoptimal utilization by allowing services to run anywhere, regardless ofrequirements or limitations that underlying platforms or operatingsystems may have. Thus, the workload management system may definestandardized partitions that control whether certain portions of theoperating system execute over hardware provided in a hostingenvironment, or inside virtual machines 114 b that decouple applicationsand services from the hardware on which the virtual machines 114 b havebeen deployed. The workload management system may further employ astandardized image for the virtual machines 114 b, provide metadatawrappers for encapsulating the virtual machines 114 b, and providevarious tools for managing the virtual machines 114 b (e.g., “zeroresidue” management agents that can patch and update running instancesof virtual machines 114 b stored in the clustered file system 195,databases 155, or other repositories).

In one implementation, the virtualized services provided in the workloadmanagement system may simplify processes for developing and deployingapplications, which may enable optimal utilization of physical resources114 a in the infrastructure. Furthermore, virtualization may be used tocertify the Linux operating environments employed in the infrastructure110 for any suitable platform that include various physical resources114 a. In particular, as described in further detail above, the workloadmanagement system may partition the Linux operating environments into amultiple-layer distribution that includes a physical distribution and avirtual distribution, wherein the physical distribution may represent alower-level interface to physical resources 114 a that host virtualmachines 114 b, while the virtual distribution may represent anyapplications or services hosted on the virtual machines 114 b.

For example, in one implementation, the physical distribution mayinclude a minimally functional kernel that bundles various base driversand/or independent hardware vendor drivers matched to the physicalresources 114 a that host the virtual machines 114 b. In oneimplementation, the physical distribution may further include apluggable hypervisor that enables multiple operating systems to runconcurrently over the hosting physical resources 114 a, a minimal numberof software packages that provide core functionality for the physicaldistribution, and one or more of the zero residue management agents thatcan manage any virtualized resources 114 b that may be hosted on thephysical resources 114 a. As such, in response to any particular requestto install a physical distribution, package selections available to theworkload management system may include packages for the kernel, thehypervisor, the appropriate drivers, and the management agents that maybe needed to support brands or classes of the underlying physicalresources 114 a.

Furthermore, in one implementation, the virtual distribution may includea tuned appliance, which may generally encapsulate an operating systemand other data that supports a particular application. In addition, thevirtual distribution may further include a workload profileencapsulating various profiles for certifying the appliance withattestation tokens (e.g., profiles for resources 114, applications,service level agreements, inventories, cost, compliance, etc.). Thus,the virtual distribution may be neutral with respect to the physicalresources 114 a included in the physical distribution, wherein thevirtual distribution may be managed independently from any physicaldrivers and applications hosted by a kernel for the virtual distribution(e.g., upgrades for the kernels and physical device drivers used in thephysical distributions may be managed independently from securitypatches or other management for the kernels and applications used in thevirtual distributions). Thus, partitioning the physical distributionsfrom the virtual distributions may remove requirements for particularphysical resources 114 a and preserve records for data that may requirea specific application running on a specific operating system.

In one implementation, from a business perspective, the workloadmanagement system may secure the virtualized resources 114 b in asimilar manner as applications deployed on the physical resources 114 a.For example, the workload management system may employ any accesscontrols, packet filtering, or other techniques used to secure thephysical resources 114 a to enforce containment and otherwise secure thevirtualized resources 114 b, wherein the virtualized resources 114 b maypreserve benefits provided by running a single application on a singlephysical server 114 a while further enabling consolidation and fluidallocation of the physical resources 114 a. Furthermore, the workloadmanagement system may include various information technology tools thatcan be used to determine whether new physical resources 114 a may beneeded to support new services, deploy new virtual machines 114 b, andestablish new virtual teams that include various collaborating entities.

In one implementation, the information technology tools may include atrending tool that indicate maximum and minimum utilizations for thephysical resources 114 a, which may indicate when new physical resources114 a may be needed. For example, changes to virtual teams, differenttypes of content, changes in visibility, or other trends for thevirtualized resources 114 b may cause changes in the infrastructure 110,such as compliance, storage, and fault tolerance obligations, whereinthe workload management system may detect such changes and automaticallyreact to intelligently manage that the resources 114 in theinfrastructure 110. In one implementation, the information technologytools may further include a compliance tool providing a complianceenvelope for applications running or services provided within anysuitable virtual machine 114 b. More particularly, the complianceenvelope may save a current state of the virtual machine 114 b at anysuitable time and then push an updated version of the current state tothe infrastructure 110, whereby the workload management system maydetermine whether the current state of the virtual machine 114 bcomplies with any policies that may have been defined for the virtualmachine 114 b. For example, the workload management system may supportdeploying virtual machines 114 b in demilitarized zones, cloud computingenvironments, or other data centers that may be remote from theinfrastructure 110, wherein the compliance envelope may provide asecurity wrapping to safely move such virtual machines 114 b and ensurethat only entities with approved identities can access the virtualmachines 114 b.

Thus, from an architectural perspective, the virtualized resources 114 bmay enable the workload management system to manage development anddeployment for services and applications provisioned in theinfrastructure 110. For example, rather than dynamically provisioningphysical resources 114 a to deal with transient peaks in load andavailability on a per-service basis, which may result in under-utilizedphysical resources 114 a, the workload management system may hostmultiple virtual machines 114 b on one physical machine 114 a tooptimize utilization levels for the physical resources 114 a, which maydynamically provisioned physical resources 114 a that enable mobilityfor services hosted in the virtual machines 114 b. Thus, in oneimplementation, mobile services may enable the workload managementsystem to implement live migration for services that planned maintenanceevents may impact without adversely affecting an availability of suchservices, while the workload management system may implement clusteringor other availability strategies to address unplanned events, such ashardware or software failures.

In one implementation, the workload management system may furtherprovide various containers to manage the virtual machines 114 b, whereinthe containers may include a security container, an applicationcontainer, a service level agreement container, or other suitablecontainers. The security container may generally providehardware-enforced isolation and protection boundaries for variousvirtual machines 114 b hosted on a physical resource 114 a and thehypervisor hosting the virtual machines 114 b. In one implementation,the hardware-enforced isolation and protection boundaries may be coupledwith a closed management domain to provide a secure model for deployingthe virtual machines 114 b (e.g., one or more security labels can beassigned to any particular virtual machine 114 b to contain viruses orother vulnerabilities within the particular virtual machine 114 b).Furthermore, in the context of tuned appliances, wherein one virtualmachine 114 b hosts one service that supports one particularapplication, the application container may package the service within aparticular virtual machine image 114 b. As such, the virtual machineimage 114 b may include a kernel and a runtime environment optimallyconfigured and tuned for the hosted service. Similarly, the servicelevel agreement container may dynamically monitor, meter, and allocateresources 114 to provide quality of service guarantees on a per-virtualmachine 114 b basis in a manner transparent to the virtual machinekernel 114 b.

In one implementation, the various containers used to manage the virtualmachines 114 b may further provide predictable and custom runtimeenvironments for virtual machines 114 b. In particular, the workloadmanagement system may embed prioritization schemes within portions of anoperating system stack associated with a virtual machine 114 b that mayadversely impact throughput in the operating system. For example,unbounded priority inversion may arise in response to a low-prioritytask holding a kernel lock and thereby blocking a high-priority task,resulting in an unbounded latency for the high-priority task. As such,in one implementation, the prioritization schemes may embed a deadlineprocessor scheduler in the hypervisor of the virtual machine 114 b andbuild admission control mechanisms into the operating system stack,which may enable the workload management system to distribute loadsacross different virtual machine 114 b and support predictablecomputing. In addition, the workload management system may decomposekernels and operating systems for virtual machines 114 b to providecustom runtime environments. For example, in the context of a typicalvirtual machine 114 b, an “unprivileged guest” virtual machine 114 b mayhand off processing to a “helper” virtual machine 114 b at a devicedriver level. Thus, to support server-class applications that may dependon having a portable runtime environment, the workload management systemmay use the decomposed kernels and operating systems to dynamicallyimplement an operating system for a particular virtual machine 114 b atruntime (e.g., the dynamically implemented operating system mayrepresent a portable runtime that can provide a kernel for a virtualmachine 114 b that hosts a service running a server-class application,which may be customized as a runtime environment specific to thatservice and application).

In one implementation, the workload management system may further employdifferent virtualization technologies in different operatingenvironments. For example, in one implementation, the workloadmanagement system may implement Type 1 hypervisors for virtualizedserver resources 114 b and Type 2 hypervisors for virtualizedworkstation, desktop, or other client resources 115. In particular, Type1 hypervisors generally control and virtualize underlying physicalresources 114 a to enable hosting guest operating systems over thephysical resources 114 a (e.g., providing coarse-level scheduling topartition the physical resources 114 a in a manner that can meet qualityof service requirements for each of the guest operating systems hostedon the physical resources 114 a). Thus, the workload management systemmay implement Type 1 hypervisors for virtualized server resources 114 bto leverage performance and fault isolation features that suchhypervisors provide. In contrast, Type 2 hypervisors generally includeuse a host operating system as the hypervisor, which use Linuxschedulers to allocate resources 114 to guest operating systems hostedon the hypervisor. In Type 2 hypervisor architectures, such as theVMware GSX Server, Microsoft Virtual PC, and Linux KVM, hosted virtualmachines 114 b appear as a process similar to any other hosted process.Thus, because workstations, desktops, and other client resources 115 mayinclude hardware that may or may not support virtualization, theworkload management system may provide centralized desktop managementand provisioning using Type 2 hypervisors. For example, the workloadmanagement system may manage and maintain desktop environments asvirtual appliances 114 b hosted in the infrastructure 110 and thenremotely deliver the desktop environments to remote client resources 115(e.g., in response to authenticating an end user at a particular clientresource 115, the virtual appliance 114 b carrying the appropriatedesktop environment may be delivered for hosting to the client resource115, and the client resource 115 may transfer persistent states for thedesktop environment to the infrastructure 110 to ensure that the clientresource 115 remains stateless).

In one implementation, orchestrated virtualization may generally referto implementing automated policy-based controls for virtualizedservices. For example, an orchestrated data center may ensure compliancewith quality of service agreements for particular groups of users,applications, or activities that occur in the information technologyinfrastructure 110. The workload management system may therefore providea policy-based orchestration service to manage virtualized resources 114b, wherein the orchestration service may gather correct workload metricswithout compromising performance in cloud computing environments orother emerging service delivery models. For example, workloads thatusers define may be executed using coordinated sets of virtual machines114 b embedding different application-specific operating systems,wherein the workload management system may provision and de-provisionthe virtual machines 114 b to meet requirements defined in the workload(e.g., using standard image formats and metadata wrappers to encapsulatethe workloads, embed standard hypervisors in the virtual machines 114 b,physical-to-virtual (P2V) or virtual-to-virtual (V2V) conversion toolsto translate between different image formats, etc.). Furthermore, incloud computing environments that can include unpredictable sets ofdynamic resources external to the infrastructure 110, the workloadmanagement system coordinate such resources using a closed-loopmanagement infrastructure 170 that manages declarative policies,fine-grained access controls, and orchestrated management and monitoringtools.

In one implementation, the workload management system may further managethe orchestrated data center to manage any suitable resources 114involved in the virtualized workloads, which may span multiple operatingsystems, applications, and services deployed on various physicalresources 114 a and/or virtualized resources 114 b (e.g., a physicalserver 114 a and/or a virtualized server 114 b). Thus, the workloadmanagement system may balance resources 114 in the informationtechnology infrastructure 110, which may align management of resources114 in the orchestrated data center with business needs or otherconstraints defined in the virtualized workloads (e.g., deploying ortuning the resources 114 to reduce costs, eliminate risks, etc.). Forexample, as described in further detail above, the configurationmanagement database 185 a may generally describe every resource 114 inthe infrastructure 110, relationships among the resources 114, andchanges, incidents, problems, known errors, and/or known solutions formanaging the resources 114 in the infrastructure 110.

As such, the policy-based orchestration service may provide federatedinformation indexing every asset or other resource 114 in theinfrastructure 110, wherein the workload management system may referencethe federated information to automatically implement policy-controlledbest practices (e.g., as defined in the Information TechnologyInfrastructure Library) to manage changes to the infrastructure 110 andthe orchestrated data center. For example, the configuration managementdatabase 185 a may model dependencies, capacities, bandwidthconstraints, interconnections, and other information for the resources114 in the infrastructure 110, which may enable the workload managementsystem to perform impact analysis, “what if” analysis, and othermanagement functions in a policy-controlled manner. Furthermore, asnoted above, the configuration management database 185 a may include afederated model of the infrastructure 110, wherein the informationstored therein may originate from various different sources. Thus,through the federated model, the configuration management database 185 amay appear as one “virtual” database incorporating information fromvarious sources without introducing overhead otherwise associated withcreating one centralized database that potentially includes largeamounts of duplicative data.

In one implementation, the orchestration service may automate workloadsacross various physical resources 114 a and/or virtualized resources 114b using policies that match the workloads to suitable resources 114. Forexample, deploying an orchestrated virtual machine 114 b for a requestedworkload may include identifying a suitable host virtual machine 114 bthat satisfies any constraints defined for the workload (e.g., matchingtasks to perform in the workload to resources 114 that can perform suchtasks). In response to identifying allocating and deploying the suitablehost virtual machine 114 b, deploying the orchestrated virtual machine114 b for the workload may include the workload management systempositioning an operating system image on the host virtual machine 114 b,defining and running the orchestrated virtual machine 114 b on thechosen host virtual machine 114 b, and then monitoring, restarting, ormoving the virtual machine 114 b as needed to continually satisfy theworkload constraints.

In one implementation, the orchestration service may include variousorchestration sub-services that collectively enable management overorchestrated workloads. For example, the orchestration service may bedriven by a blueprint sub-service that defines related resources 114provisioned for an orchestrated workload, which the workload managementsystem may manage as a whole service including various different typesof resources 114. Furthermore, a change management sub-service mayenable audited negotiation for service change requests, including themanner and timing for committing the change requests (e.g., within anapproval workload 130). The sub-services may further include anavailability management sub-service that can control and restartservices in a policy-controlled manner, a performance managementsub-service that enforces runtime service level agreements and policies,a patch management sub-service that automatically patches and updatesresources 114 in response to static or dynamic constraints, and acapacity management sub-service that can increase or reduce capacitiesfor resources 114 in response to current workloads.

To provide exemplary contexts for some of the orchestration sub-servicesnoted above, the availability management sub-service may automaticallymigrate a virtual machine 114 b to another physical host 114 a inresponse to a service restart failing on a current physical host 114 amore than a policy-defined threshold number of times. With respect tothe performance management sub-service, in response to determining thata service running at eighty percent utilization can be cloned, theservice may be cloned to create a new instance of the service and thenew instance of the service may be started automatically. Furthermore,to manage a patch for running instances of a service, the patchmanagement sub-service may test the patch against a test instance of theservice and subsequently apply the patch to the running service instancein response to the test passing. Regarding the capacity managementsub-service, an exemplary service instance may include a service levelagreement requiring a certain amount of available storage for theservice instance, wherein the capacity management sub-service mayallocate additional storage capacity to the service instance in responseto determining that the storage capacity currently available to theservice instance has fallen below a policy-defined threshold (e.g.,twenty percent).

In one implementation, the orchestration service may incorporateworkflow concepts to manage approval workloads 130 or other managementworkloads, wherein a workload database 185 b may store information thatthe workload management system can use to manage the workloads. Forexample, in one implementation, an approval workload 130 may include arequest to provision a particular service to a particular user inaccordance with particular constraints, wherein the approval workload130 may include a sequence of activities that includes a suitablemanagement entity reviewing the constraints defined for the service,determining whether any applicable policies permit or prohibitprovisioning the service for the user, and deploying the service inresponse to determining that the service can be provisioned, among otherthings. Thus, the workload engine 180 a may execute the orchestrationservice to map the sequence of activities defined for any particularworkload to passive management operations and active dynamicorchestration operations. For example, the workload database 185 b maystores various declarative service blueprints that provide master plansand patterns for automatically generating service instances, physicaldistribution images and virtual distribution images that can be sharedacross the workload management system to automatically generate theservice instances, and declarative response files that define packagesand configuration settings to automatically apply to the serviceinstances.

Collaboration

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may enable collaboration between entities that interact with theservices provided in the information technology infrastructure 110. Inparticular, collaboration may generally involve dynamic teams that crosstraditional security and policy boundaries. For example, where looselyaffiliated organizations share data and applications, the workloadmanagement system may enable continued collaboration even when some ofthe participants sharing the data and applications may be temporarilyoffline (e.g., the workload management system may authorize certainusers to allocate portions of local client resources 115 to supportcross-organizational endeavors). Thus, the workload management systemmay provide a standard interface 160 designed to enable dynamiccollaboration for end users that simplify interaction with complexsystems, which may provide organizations with opportunities for moreproductive and agile workloads.

In one implementation, the workload management system may provide acollaboration service that enables workloads to span multiple users,applications, services, systems, or other resources 114. For example,multiple users may collaborate and share data and other resources 114throughout the workload management system, both individually and withinvirtual teams (e.g., via a service bus that transports data relating toservices or other resources 114 over the event bus 140). As such, theworkload management system may support virtual team creation that canspan organizational and geographic boundaries, wherein affiliations,content, status, and effectiveness may be represented for identitiesthat have membership in any particular virtual team (e.g., to enableonline and offline interaction between team members). In oneimplementation, the workload management system may provide enrichedcollaboration content (e.g., images, video, text, data feeds), and mayefficiently transport the collaboration content between team members(e.g., via the service bus). Furthermore, the workload management systemmay integrate desktops, laptops, personal digital assistants, smartphones, or other suitable client resources 115 into virtual teamcollaboration experiences in order to meet emerging demands for mobile,interoperable, and integrated access. Thus, the collaboration enabled inthe workload management system may operate in an adaptive collaborativeenvironment, which may unify technologies for online integrated mediasharing with offline authoring and editing.

In one implementation, the collaboration service may generally include aweb-based platform that support inter-organization andintra-organization management for virtual teams, interoperabilitybetween various different collaboration products, social networking todeliver information that enables the virtual teams to interactefficiently either online or offline, and federated searches against anysuitable information source, among other things. For example, in oneimplementation, the collaboration service may include variouscollaboration sub-services that collectively enable the adaptivecollaborative environment, including a client sub-service, anaggregation sub-service, an information sub-service, a real-timecollaboration sub-service, and a metadata sub-service.

In one implementation, the client sub-service may provide communicationinterfaces with real-time online systems, offline systems, and userinterfaces. In particular, functionality for the client sub-service maybe provided in a web-based interface that supports interaction with thereal-time online systems in addition to software that can executelocally at client resources 115 to provide offline access to shared dataand real-time meetings that may involve shared applications and shareddesktops. For example, in one implementation, the client sub-service maycommunicate with the aggregation sub-service to coordinate thecommunication and collaboration across various information sources,wherein the aggregation sub-service may route messages to theappropriate information sources in appropriate formats. Furthermore, toensure that collaborative contexts reference information that may bedistributed across the infrastructure 110 rather than hosted within oneparticular application, the information sub-service may integrate thedifferent information sources within the collaborative environment. Assuch, the virtual teams may connect and collaborate using informationthat originates anywhere across the infrastructure 110, and theinformation sub-service may enable members of the virtual teams todiscuss information or other content from the various sources in aninteractive manner. The real-time collaboration sub-service may interactwith the information sub-service to provide real-time meetings thatinclude audio content, video content, instant message content, and otherforms of communication content in real-time collaborative contextswithin the infrastructure 110 and with third-parties.

In one implementation, the metadata sub-service may provide a “helper”service to the aggregation and information sub-services, collectingancillary metadata generated during interaction between virtual teammembers and create collaborative threads to maintain contexts thatgenerated the data. Furthermore, the metadata sub-service may evaluatethe ancillary metadata to discover new and relevant links betweeninformation sources and integrate data that can potentially originatefrom various disparate information sources. For example, the metadatasub-service may provide a uniform format for classifying data collectedduring collaborative contexts, which may provide a single source forvirtual team members to search and display the data across any suitablecollaboration source. Similarly, the metadata sub-service may index andunify data collected from disparate network sources, including varioussearch engines and content aggregation services, to help the virtualteam members to locate information that may be interesting or otherwiserelevant to the collaborative contexts. As such, the varioussub-services integrated within the collaboration service may provide acollaborative environment that supports dynamic interaction acrossorganizational boundaries and different information sources in a mannerthat can account for any particular virtual team member's personalpreferences.

Architectural Agility

In one implementation, as noted above, the technologies integrated bythe model-driven architecture 100A and the service-oriented architecture100B may collectively provide various services that the workloadmanagement system can use to manage workloads and enable intelligentchoices in an information technology infrastructure 110. Furthermore,various horizontal integration components may be distributed in theworkload management system to integrate the various technologiesemployed in the model-driven architecture 100A and the service-orientedarchitecture 100B and provide an agile and interoperable informationtechnology infrastructure 110.

In particular, the horizontal integration components distributed acrossthe workload management system may provide agility and interoperabilityto the information technology infrastructure 110 through support forvarious emerging service delivery models, including Web 2.0, Software asa Service (SaaS), mashups, hardware, software, and virtual appliances,cloud computing, grid computing, and thin clients, among others. Forexample, in one implementation, every service, application, or otherresource 114 in the workload management system may be provided with anapplication programming interface 160 that can provide connectivitybetween different operating systems, programming languages, graphicaluser interface toolkits, or other suitable services, applications, orresources 114.

In one implementation, the application programming interface 160 mayinclude a Representational State Transfer (REST) application programinterface 160, which may use standard methods defined in the HypertextTransfer Protocol (HTTP), wherein using standardized types to formatdata may ensure interoperability. In one implementation, the RESTinterface 160 may define a Uniform Resource Identifier (URI) thatrepresents a unique identity for any suitable entity, and may furtherdefine relationships between the represented identities with hyperlinksthat can be selected to access information for related identities,attribute claims, roles, policies, workloads, collaboration spaces, andworkflow processes. Thus, through the use of URIs, hyperlinks, and otherstandard HTTP methods, the REST interface 160 may provide an interfaceto a data ecosystem that can be navigated in a web-based environmentthat can be used anywhere in the workload management system. In oneimplementation, the REST interface 160 may declare a namespace havingversion controls and standard methods to read and write to the dataecosystem, and may include a URI registry containing the URIs thatrepresent the identities in the data ecosystem. Thus, any suitableresource 114 may programmatically discover other identities thatcommunicate using the REST interface 160 (e.g., the REST interface 160may be implemented in a communication gateway 112 a to physicalresources 114 a, a communication gateway 112 b to virtualized resources114 a, a communication gateway 112 c to configuration resources 114 c,etc.).

Furthermore, in one implementation, the workload management system mayextend an application program interface stack for the supplied RESTinterface 160, which may enable new services, applications, and otherresources 114 to be integrated into the workload management system in amanner that automatically inherits the identity-based andpolicy-controlled services implemented in the workload managementsystem. In particular, the supplied application program interface stackmay generally include a unified adapter and a proxy to existing andfuture technologies using protocols to enable services that communicatethrough the REST interface 160 regardless of whether the services residein the infrastructure 110, a cloud computing environment, a third partydata center, or elsewhere (e.g., web service protocols, lightweightdirectory protocols, messaging queue protocols, remote procedure callprotocols, etc.). To provide support to developers and users that extendthe application program interface stack supplied for the REST interface160, a Recipe-based Development Kit (RDK) may provide full source codeexamples for various operating systems, programming languages, andgraphical user interface toolkits.

Additionally, in one implementation, the workload engine 180 a maymanage creation of application program interface keys for the RESTinterface 160 stack, whereby auditing and policy-based approvals may besupported for provisioning the application program interface keys. Forexample, the workload management system may deploy widgets to clientdesktops 115, wherein the widget may track identities and contexts thatinclude attempts to access the REST interface 160 stack. Thus, inresponse to provisioning or auditing application program interface keys,platform authentication and policy checks may be triggered against theaccessing identity and the context that the keys supply. In a similarmanner, the application program interface keys may enable the workloadmanagement system to meter costs for the information technologyinfrastructure 110.

Thus, the standardized stack supplied for the REST application programinterface 160 may provide support for industry standard authenticationand authorization methods, which may enable identity-managed andpolicy-controlled auditing for events and access controls. Furthermore,the extensibility of the REST application program interface 160 mayenable integration with any suitable existing or future-developedsystem. For example, in one implementation, the REST interface 160 maybe configured with standards such as the Atom Syndication Format andAtom Publishing Protocol to integrate feed synchronization, JavaScriptObject Notation and Extensible Markup Language (XML) to integrateenterprise portals, mashups, and social networking platforms. Thus, inthe context of feed synchronization to provide automaticallynotifications in response to any changes to a particular resource 114, auser may simply enter a URI for the resource 114 in an existing webbrowser feed aggregator (e.g., Firefox bookmarks). Thus, by providingextensible support for any suitable system, application, service, orother resources 114, the features of the REST application programinterface 160 may provide agility and interoperability to theinfrastructure 110.

Having described the model-driven and service-oriented architecture100A-B that collectively provide the agile, responsive, reliable, andinteroperable environment that enables the features of the workloadmanagement system, the description to be provided below will addresscertain particular features of the workload management system. Inaddition, further detail relating to the architectural foundation andother features of the workload management system may be provided in“Novell Architectural Foundation: A Technical Vision for Computing andCollaborating with Agility,” “Automation for the New Data Center,” and“A Blueprint for Better Management from the Desktop to the Data Center,”the contents of which are hereby incorporated by reference in theirentirety.

According to one aspect of the invention, FIG. 2 illustrates anexemplary method 200 for intelligent workload management. In particular,the intelligent workload management method 200 may be used to manageapproval workloads created in response to service requests. Inparticular, an operation 210 may include creating an approval workloadin response to a receiving a request for a service from any suitableuser, application, system, or other entity having an identity in theworkload management system. For example, in one implementation, therequest may generally specify any components needed to configure theservice for a particular task (e.g., a raw machine hosting an operatingsystem and storage may be requested to deploy a particular applicationin the raw machine, an existing service may be requested to specify anysuitable combination of components that can deploy the application,etc.). In addition, the request may further specify desired aperformance level (or service level) for the service (e.g.,availability, release capacity, financial constraints, continuity,etc.), any comments for provisioning the service in a certain manner(e.g., provision the service as soon as possible, according to aparticular schedule or policy, to particular members in a virtual team,with a particular configuration, etc.).

Thus, in one implementation, the request may generally include anysuitable criteria that the requesting entity specifies to defineconstraints for deploying the requested service, wherein the workloadmanagement system may create the approval workload in operation 210 todetermine whether or not the requested service can be provisioned in amanner that meets the constraints defined in the request. For example,in one implementation, the approval workload may generally define a taskthat includes various human and/or automated approvers (or servicedelivery managers) collaboratively managing the service request todetermine whether the service can be provisioned as requested. Thus, tomanage the approval workload, an operation 220 may include the workloadmanagement system querying a configuration management database to obtainan infrastructure model describing any computing resources and storageresources available to run the requested service.

In one implementation, the model of the computing resources obtained inoperation 220 may include various rack-mounted servers and/or bladeservers, which may include multi-core processors (e.g., sixty-four bitprocessors), a multiple gigabyte local memory, a serial-attachedRedundant Array of Independent Disks (RAID), Ethernet and Storage AreaNetwork (SAN) interfaces, and embedded hardware that can supportvirtualization. In addition, the computing resources may further run anappropriate operating system for the underlying physical architecture,including a virtual machine monitor (e.g., a hypervisor), various devicedrivers, a management kernel, and any suitable management agents. In oneimplementation, the management kernel and the management agents maycollectively provide support for remotely deploying virtual machines tobe executed by the hypervisors present on the computing resources, whichmay enable the workload management system to group and organize thecomputing resources. For example, a globally unique identifier (e.g., aURI) may be created for each of the computing resources, whereby thecomputing resources may be grouped or otherwise organized according toany suitable combination of a type (e.g., thin blade, symmetricmultiprocessing, etc.), intended purpose (e.g., test, production, etc.),owner, physical location, or other classifying types. Furthermore, theworkload management system may configure one or more of the computingresources to function in isolation or cooperatively with other computingresources to create high-availability clusters.

In one implementation, the model of the storage resources obtained inoperation 220 may include various SAN disk-block storage arrays and/orfile servers, whereby the storage resources may be collectively pooledand protected with identity-based policy controls. In oneimplementation, the computing resources described above may access thestorage resources on behalf of virtual machines deployed in theinfrastructure, wherein the storage resources may be individuallymanaged during lifecycles of the virtual machines in a dynamic manner.Furthermore, the workload management system may group and organize thestorage resources in a similar manner as the computing resources,wherein the workload management system may manage the storage resourcesaccording to any suitable combination of a type (e.g., available RAID-5disks), intended purpose (e.g., temporary, protected, remotelyreplicated, etc.), owner, physical location, or other classifying types.

In one implementation, the model of the computing resources and thestorage resources obtained in operation 220 may further include variousrelationships between the resources, wherein the relationships mayinclude dependencies, capacities, and bandwidth requirements. Forexample, any particular virtual machine deployed in the infrastructuremay generally run on physical computing resources, wherein the model mayinclude federated information that links a network address, identities,and other information for the virtual machine with any computingresources and storage resources that have been allocated to the virtualmachine, which may enable lifecycle management for the virtual machine.Thus, the configuration management database may generally providefederated knowledge detailing any suitable entity managed in theworkload management system and relationships between such managedentities.

In one implementation, in response to querying the configurationmanagement database in operation 220 to obtain the current model of theinfrastructure, an operation 225 may determine whether the workloadmanagement system can provision the service requested in the approvalworkload in a manner that meets any constraints that the request definedfor the service. In particular, the workload management system maydetermine whether the infrastructure model indicates that theinfrastructure has available computing resources and storage resourcessuitable to provision the requested service. Furthermore, the workloadmanagement system may employ the identity management and policyenforcement services to determine whether the service can be provisionedto the requesting entity without violating any relevant policies. Forexample, to authenticate and configure a desktop machine for a chieffinancial officer, a biometric authorization component (e.g., afingerprint reader) may be installed in the desktop machine. Thus, theidentity management and policy enforcement services may collectivelyprohibit the workload management system from deploying services to thedesktop machine that would add a keystroke logger, remove the biometricauthorization component, or violate another policy with respect to thechief financial officer identity. In another example, requests for BitTorrent storage may be denied regardless of an identity for therequesting identity because a policy prohibits peer-to-peer filesharing.

Thus, in response to the workload management system determining inoperation 225 that the requested service cannot be provisioned inaccordance with the constraints defined in the request (e.g., becausethe infrastructure lacks sufficient computing resources and/or storageresources to support the service, the requested service violates arelevant policy with respect to an identity for the requesting entity,etc.), the workload management system may deny the request and send anappropriate denial notification to the requesting entity in an operation230. For example, the denial notification may provide a reason fordenying the service request, which may provide information that can bereferenced to analyze subsequent requests having similar criteria,modify the request based on available resources or relevant policies,audit approval processes in a compliance review, or otherwisereferenced.

On the other hand, in response to determining in operation 225 that therequested service can be provisioned in accordance with the requestedconstraints (e.g., because the infrastructure has sufficient computingresources and storage resources to support the service, the requestedservice does not violate any policies with respect to the identity forthe requesting entity, etc.), the workload management system may approvethe request and then initiate provisioning for the service in anoperation 235. In particular, in response to approving the request, theworkload management system may reserve appropriate physical computingresources, virtual computing resources, and/or storage resources to runthe service, wherein operation 235 may include determining whether suchresources can be automatically and/or immediately allocated. Forexample, certain workloads may be prioritized to ensure that businessobjectives can be met, wherein the workload management system may deferthe approval workload in operation 235 in response to determining thatallocating the resources to the approval workload may occupy resourcesneeded for higher priority workloads (e.g., because the reservedresources are currently subject to a “blackout” period for patching orupdating the resources).

As such, in response to determining that the resources reserved to theservice cannot be provisioned automatically and/or immediately, theworkload management system may manage creation of a provisioning planfor the service in an operation 240. In particular, operation 240 mayinclude various automated and/or human entities interacting to createthe provisioning plan, wherein the provisioning plan may includepre-empting the approval workload until workloads in a high priorityqueue have completed, moving the approval workload to the high priorityqueue, dynamically allocating additional resources to the approvalworkload (e.g., pre-empting lower priority workloads), or otherwisebalancing utilization of the resources in the infrastructure betweenbusiness processes and system processes that may have differentpriorities. Furthermore, in one implementation, the workload managementsystem may coordinate the interaction between the entities that createthe provisioning plan in operation 240 (e.g., because the service cannotbe provisioned until a certain process has completed, a certain entityprovides feedback, etc.). As such, operation 240 may generally includevarious processes and interactions between entities, which the workloadmanagement system may manage to create the plan for suitablyprovisioning the approved service.

In one implementation, in response to determining that the resourcesreserved to the service can be provisioned automatically andimmediately, or alternatively in response to successfully creating theprovisioning plan for the service in operation 240, the workloadmanagement system may provision the requested service in an operation250. In particular, operation 250 may include allocating an operatingsystem image, a resource inventory, and software to an orchestratedvirtual machine that can run the service and embedding lifecycle controlinformation within the orchestrated virtual machine to enable managementfor the virtual machine and the computing resources allocated to theservice. In one implementation, one or more of the computing resourcesin the infrastructure may be configured as an image creation server,wherein the image creation servers may be dedicated to creating andinstalling virtual machines in various ways. For example, in a largeinformation technology infrastructure that frequently creates virtualmachine instances, multiple image creation servers may be employed tocreate and install the virtual machines, or one or more of the imagecreation servers may be configured to create “in-place” virtualmachines, wherein such virtual machines may be incubated on particularcomputing resources that further execute the virtual machines.

Thus, in one implementation, operation 250 may include invoking an imagecreation service, which may create a virtual machine image to run therequested service. For example, the image creation service may contactan image repository that contains various ready-to-run virtual machineimages and then appropriately download one or more of the virtualmachine images that can run the requested service. The image creationservice may then clone and configure the virtual machine imagedownloaded from the image repository based on any constraints that therequest defines for the service. As such, operation 250 may generallyinclude creating a new virtual machine having an operating system image,external storage references, and control information particularlyconfigured for the requested service (e.g., based on identities,policies, service level agreements, lifecycle management, etc.), and mayfurther include deploying the newly created virtual machine to computingresources that have been reserved to run the requested service.Alternatively (or additionally), the image creation service may providea push model for deploying the virtual machine image, wherein the imagecreation service may instruct the image repository to multi-cast theimage to multiple computing resources. Thus, the push modelimplementation may pre-stage the multi-casted virtual machine image fordeployment over various potential deployment targets.

In one implementation, in response to successfully provisioning theservice in operation 250, the workload management system may update theinfrastructure model in an operation 260. For example, any resources,identities, policies, or other information associated with theprovisioned service may be indexed within a global namespace in thefederated configuration management database. As such, the workloadmanagement system may reference the updated infrastructure model totrack registered virtual machines that have been provisioned anddeployed in the infrastructure, hierarchical relationships between theregistered virtual machines and the resources, identities, policies, orother information associated with the virtual machines, and otherwiseprovide lifecycle management for the virtual machines, as will bedescribed in greater detail below. Furthermore, an operation 270 mayinclude the workload management system sending a service provisioningnotification to the requesting entity, wherein the notification sent inoperation 270 may indicate that the service has been successfullyprovisioned, provide information that can be referenced to analyzesubsequent requests having similar criteria, audit approval processes ina compliance review, or otherwise provide information relevant to theprovisioned service.

In one implementation, the workload management system may manage theprovisioned service in an operation 280 in response to successfullyprovisioning the service in operation 250. In particular, as notedabove, updating the infrastructure model in operation 260 may provideinformation that the workload management system can reference to providelifecycle management for services provisioned and deployed in theinfrastructure. For example, various lifecycle rules and controlinformation may be used to respond to variable computing demands,changes, and unexpected events in the infrastructure, wherein servicesthat run within virtual machines may introspectively monitor and reporton health of the hosted services. Thus, the provisioned service may bemanaged in operation 280 with the lifecycle control information embeddedin the host virtual machines (e.g., monitoring real-time executionstates and other health conditions, automatically managing identitiesand policies in response to monitored health conditions, retiringresources reserved or allocated the virtual machine that may no longerbe needed, etc.).

In addition, the workload management system may cooperate with thelifecycle controls embedded in the host virtual machines to manage theprovisioned service. In particular, the workload management system mayaggregate information relating to the monitored states reported fromindividual virtual machine instances and record such information withina context describing a current state of the infrastructure model. Thus,physical constraints, dependencies, current performance trends, andother real-time execution states may be monitored to schedule virtualmachines that run provisioned services to computing resources forexecution in a manner that satisfies any identity constraints, policycontrols, service level agreements, or other constraints that have beendefined for the services. For example, operation 280 may includeapplying policy-defined thresholds to any status events generated by themonitored computing resources, storage resources, virtual machines, orother resources (e.g., responding to a monitored variable that exceedsor falls below a policy-defined threshold for more than a policy-definedtime period). In another example, operation 280 may further includemanaging version controls for virtual machine images, which may providesupport for inserting management agents that can tune or patch thevirtual machine images as needed, and rolling the virtual machine imagesback to a “pristine” state, among other things.

Thus, the techniques described above the intelligent workload managementmethod 200 may generally provide lifecycle management from creating avirtual machine image that can host a requested service through eventualretirement of the virtual machine image. Moreover, in addition tointrospective health monitoring and maintenance for individual virtualmachine images, the lifecycle management techniques may providefederated information for managing an entire information technologyinfrastructure, which may be used to assure compliance with legal andcontractual obligations for any suitable hardware or software that anorganization may use, create detailed plans for implementing or rollingback proposed changes to the infrastructure, detect, resolve, andotherwise remediate incidents in the infrastructure, reactively andproactively manage problems in the infrastructure with knownworkarounds, fixes, and permanent infrastructure changes, and ensurethat every service in the infrastructure meets or exceeds service levelrequirements, among other things.

According to one aspect of the invention, FIG. 3 illustrates anexemplary system 300 for discovering enriched information technologymodels in the intelligent workload management system. In oneimplementation, the information technology models may be enriched withworkload entitlements derived from single sign-on workload identities,which may be generated from authentication tokens that define variouscredentials or permissions assigned to any suitable user, application,system, service, resource, or other entity having an identity managed inthe workload management system. In particular, as described in furtherdetail above in connection with FIG. 1A-B and FIG. 2, the workloadmanagement system may generally provide various services that integrateinformation technologies for identity management, policy enforcement,compliance assurance, managing physical computing and storage resources,orchestrating virtual machines that run on the physical computingresources and reference the physical storage resources, enablingcollaborative virtual teams, and providing architectural agility, amongother things. The workload management system may therefore include amanagement infrastructure 370 having a workload engine 380 a that candynamically allocate physical resources to host virtual machines thatrun applications and services supporting infrastructure workloads, whichmay enable a distributed and virtualized data center that enablesmobility for any suitable client device 315.

As such, to manage mobility for client devices 315 or other resources inthe distributed and virtualized data center, the workload engine 380 amay use at least the integrated identity management technologies tosecurely name, associate, authenticate, and authorize identities thatmay consume applications and services in the workload management system.More particularly, in one implementation, managed identities may bestored in a federated identity vault 325 that provides a context to bindinformation technology processes managed by the workload engine 380 a(e.g., from a service request that a particular entity provides to datathat the request targets in the physical storage resources). Forexample, the identity vault 325 may contain various managed identitiesthat grant users rights or permissions to applications, services, orother resources, and the identity vault 325 may further contain variousmanaged identities that grant the applications, services, or otherresources rights or permissions to other applications, services, orresources. Moreover, the managed identities stored in the identity vault325 may define various different roles for the represented entities,whereby the identity vault 325 may define federated rights, permissions,or other credentials granted to represented entities across variousauthentication domains. Thus, the system 300B may employ variousidentity data abstractions maintained in the federated identity vault325 to generate workload entitlements that can enrich discovery in theworkload management system (e.g., single sign-on authentication tokensgenerated by an authentication server).

For example, the management infrastructure 370 may further include adiscovery engine 380 b that can identify and describe an operationalstate for any resource in an actual model 310 a of the informationtechnology infrastructure. In one implementation, the discovery engine380 b may any suitable agent-based technique or agent-less technique todiscover physical devices in the actual infrastructure model 310 a, suchas an Internet Control Message Protocol (ICMP) ping, a Simple NetworkManagement Protocol (SNMP) Get, or Transmission Control Protocol (TCP)port probing, among others. As such, the discovery engine 380 b maydiscover various types of information to identify and describe thephysical devices in the actual infrastructure model 310 a. For example,the information discovered for the physical devices may includeprocessor types, reboot capabilities, virtualization capabilities,hardware components, out-of-band management capabilities, power supplyratings, or other information. Additionally, the discovery engine 380 bmay further discover various types of information to identify anddescribe applications running in the actual infrastructure model 310 a.For example, in one implementation, the discovery engine 380 b may useapplication fingerprinting to discover the applications running in theactual infrastructure model 310 a, wherein the applicationfingerprinting may include matching artifacts or other informationdiscovered for the physical devices with predetermined applicationattributes that identify and describe the applications (e.g., filelocations, registry settings, service signatures, etc.).

Furthermore, in one implementation, the discovery engine 380 b maydiscover workload entitlements or various other dependencies between theapplications, physical devices, and other resources in theinfrastructure to discover the applications and services running in theactual infrastructure model 310 a. In particular, applications maygenerally include one or more aggregated services, while services maygenerally include one or more aggregated resources, whereby thedependencies discovered in the actual infrastructure model 310 a mayidentify and describe any applications configured to interact withservices actively running in the actual infrastructure model 310 a. Inparticular, in one implementation, the services running in the actualinfrastructure model 310 a may be hosted by various virtual machinesthat run on the physical devices discovered in the infrastructure. Thus,the dependencies discovered by the discovery engine 380 b may includerelationships between identities that define workload entitlements forthe virtual machines, the physical devices that host the virtualmachines, any applications that the virtual machines execute, any usersthat interact with the virtual machines or the applications that thevirtual machines execute, or any other suitable entity having anidentity managed in the workload management system. For example, therelationships may include network addresses, storage locations, capacityand bandwidth requirements, lifecycle control information, or otherinformation associated with the unique identities that define theworkload entitlements for the virtual machines, which may definedependencies between the identities for the virtual machines and theidentities for the applications, physical devices, users, or otherentities discovered in the actual infrastructure model 310 a.

As such, in one implementation, the actual infrastructure model 310 adiscovered by the discovery engine 380 b may include discovered physicaldevices, applications, services, and other resources, managed identitiesfor the discovered physical devices, applications, services, and otherresources, and relationships or other dependencies between thediscovered physical devices, applications, services, and otherresources. In one implementation, a snapshot of the actualinfrastructure model 310 a may then be persistently stored in afederated configuration management database 385 a that provides versioncontrols and other features for managing the infrastructure model 310.For example, the configuration management database 385 a may furthercontain a planned version of the infrastructure model 310 b thatincludes planned changes to the infrastructure, whereby the managementinfrastructure 370 can monitor the actual infrastructure model 310 a andcompare the actual infrastructure model 310 a to the plannedinfrastructure model 310 b to determine whether the planned changes havebeen properly implemented. In addition, the configuration managementdatabase 385 a may further contain previous versions of theinfrastructure model 310, whereby the management infrastructure 370 canmanage remediation workloads to restore previous versions of theinfrastructure model 310 in response to problems or other incidents inthe actual infrastructure model 310 a. Thus, the configurationmanagement database 385 a may maintain various versions of theinfrastructure model 310 to provide federated knowledge for managingactual operational states, configuration states, prior states, or otherstates for the infrastructure.

In one implementation, the federated infrastructure knowledge maintainedin the configuration management database 385 a may be further integratedwith a help desk system 380 c that can provide known errors andsolutions, problem histories, workarounds, and temporary fixes that canbe referenced to resolve minor incidents without having to contact humanpersonnel at the help desk system 380 c. For example, in response toexperiencing an incident or other problem with the client device 315 oranother resource in the infrastructure, a user may submit a troubleticket detailing the incident to the help desk system 380 c, which mayattempt to automatically identify any information in the configurationmanagement database 385 a that can be used to resolve the incident(e.g., matching the incident to a similar error in the problem historiesand returning a known solution, workaround, or temporary fix thatpreviously resolved the similar error). In another example, in responseto the discovering a particular service running on a particular port,enriching such discovery with workload entitlements may be used todetermine whether a user running the service has the appropriateentitlements to run the service on the particular port. Thus, the helpdesk system 380 c may provide various automated remediation proceduresthat can discover problems in the infrastructure, which may be reportedto the workload engine 380 a to fix or otherwise remediate the problemsin a remediation workload.

For example, in one implementation, the workload engine 380 a mayreference a workload database 385 b in response to receiving a reportedproblem from the help desk system 380 c, wherein the workload engine 380a may retrieve a previous remediation workload that can be employed toremediate the problem, or the workload engine 380 a may add a newremediation workload to the workload database 385 b and manage theremediation workload to remediate the problem. In particular, theremediation workloads that the workload engine 380 a manages may includeany suitable combination of automated and human intervention, whereinthe workload engine 380 a may coordinate interaction between variousautomated systems and human entities to remediate the problem, asappropriate. For example, remediating an issue such as disaster failovermay include automatically migrating services to recovery resources,whereas diagnosing, troubleshooting, or remediating a problematicapplication may primarily include interaction between human personnel,while other problems may include suitable combinations of automaticintervention and human intervention. In this context, the managedidentities may bind remediation workloads to certain entities, such thatthe workload database 385 b may detail information relating toidentities involved in the problems and any resolution to the problems.

In one implementation, the federated infrastructure knowledge maintainedin the configuration management database 385 a may further provide themanagement infrastructure 370 with information for managing plannedchanges to the infrastructure. In particular, the federatedinfrastructure knowledge may detail managed identities, servicecomponents, and dependencies in the infrastructure, which may bereferenced to determine best practices for implementing the plannedchanges. For example, in one implementation, discovered informationstored in the configuration management database 385 a may be used toprepare an organization for a Payment Card Industry (PCI) compliancereview, wherein the discovery engine 380 b may discover data detailingevery resource and managed identity that interacts with PCI credit cardinformation and export the data to a suitable database for furtheranalysis. In another example, the discovered information may be used toprepare a service for deployment to a cloud computing environment, inwhich case application fingerprinting may be executed for the service todiscover every dependency for the service, construct a cloud packagingscenario for the service, and send a notification to any managedidentities that may be impacted by deploying the service to the cloudcomputing environment. In yet another example, the discoveredinformation may be used to reduce costs for maintaining an application,wherein fingerprinting for the application may be executed to discoverevery instance of the application, managed identities that use theapplication instances, and create an elimination or consolidation planbased on comparative values, utilizations, and costs for maintaining theapplication instances (e.g., if twenty-thousand users interact with oneinstance of the application at a cost of $1,000,000, while two usersinteract with a second instance of the application at a cost of$500,000, the second instance may be recommended for elimination orconsolidation with the first instance).

According to one aspect of the invention, FIG. 4 illustrates a flowdiagram of an exemplary method 400 for generating scorecards tovisualize and tune services in the workload management system. Inparticular, and as described in further detail above, the workloadmanagement system may generally include a federated configurationmanagement database that contains various version-controlled models ofan information technology infrastructure, including previous versions ofthe infrastructure model, a current operational version of theinfrastructure model, and planned or proposed versions of theinfrastructure model. For example, in one implementation, theversion-controlled infrastructure models stored in the federatedconfiguration management database may describe every resource, asset, orother suitable configuration items in the infrastructure, includingdependencies or other relationships between the resources, assets, orother configuration items in the infrastructure. Thus, in the context ofthe method 400 illustrated in FIG. 4 and described herein, a currentstate of the information technology infrastructure and theversion-controlled infrastructure models stored in the configurationmanagement database may be analyzed to generate various scorecards thatcan be used to visualize and tune services in the workload managementsystem.

In one implementation, the workload management system may invoke adiscovery engine in an operation 410, wherein the discovery engine maydetermine a current operational state for the infrastructure. Inparticular, determining the infrastructure operational state inoperation 410 may include the discovery engine deriving various types ofinformation from the infrastructure that can inform choices for managingthe infrastructure in a manner that suits the needs of a particularbusiness. For example, in one implementation, the operational statedetermined for the infrastructure in operation 410 may describe variousservices, applications, workloads, or other resources running in theinfrastructure, including identities, operational dependencies, or otherrelationships between the various services, applications, workloads, orother resources in the infrastructure (e.g., from information containedin an identity vault). Furthermore, in one implementation, theconfiguration management database may index the running services,applications, workloads, or other resources with various parameters(e.g., business value, usage, cost, security, risk, performance, etc.),wherein the indexing parameters in the configuration management databasemay be derived from monitored activity in the infrastructure. Forexample, in one implementation, a management infrastructure may employvarious techniques to sniff packets or activity that occurs in theinfrastructure to determine managed identities having entitlements toaccess certain services, applications, workloads, or other resources inthe infrastructure, and further to derive metrics that describe themanaged identities actually access to the entitled resources (e.g.,whether or not certain managed identities have been accessing theentitled resources, frequencies that described how often certain managedidentities have been accessing the entitled resources, etc.) As such,the operational state determined in operation 410 may include varioustypes of information that describe the resources in the infrastructureand activity associated with the resources, which may then be used togenerate various scorecards for visualizing and tuning the services,applications, workloads, or other resources in the infrastructure.

In one implementation, the various scorecards for visualizing and tuningthe services, applications, workloads, or other resources in theinfrastructure may include a service listing scorecard, which may begenerated in an operation 420. In particular, FIG. 5A illustrates anexemplary instance of the service listing scorecard that may begenerated in operation 420, wherein the service listing scorecard may beused to visualize and tune costs in the infrastructure. The servicelisting scorecard may generally describe every service, application, andworkload discovered in the infrastructure, which may be scored with theindexing parameters that describe the business value, usage, and costfor the discovered services, applications, and workloads. For example,the exemplary service listing scorecard shown in FIG. 5A describes afirst SAP service instance indexed with the identifier 101, a second SAPservice instance indexed with the identifier 103, and a PeopleSoftservice instance indexed with the identifier 201. However, the servicelisting scorecard illustrated in FIG. 5A will be understood as providinga limited number of service instances for ease of description, as theservice listing scorecard may include many additional entries describingvarious other services, applications, and workloads that may be runningin the infrastructure, as appropriate.

In one implementation, the service instances described in the servicelisting scorecard may further include resource names that describecontexts for the service instances. For example, the service listingscorecard shown in FIG. 5A indicates that the first instance 101 of theSAP service provides an accounts payable (AP) resource, the secondinstance 103 of the SAP service provides an information services andtechnology (IS&T resource service, and the instance 201 of thePeopleSoft service provides a human resources (HR) resource.Additionally, the service listing scorecard may visualize businessvalues, usages, and costs for the various service instances. Forexample, in one implementation, the business values may be expressedwithin a range of numeric values (e.g., from one, representing a lowestbusiness value, to five, representing a highest business value), whilethe usages may be expressed in a numeric value (e.g., derived from anumber of users authorized to interact with the service, a number ofusers that actually interact with the service, utilization metrics thatrepresent actual usage versus total capacity, etc.). Furthermore, theservice listing scorecard may provide estimated costs for the serviceinstances, wherein the estimated costs may be derived from any resourcesin the infrastructure that support the service (e.g., costs forobtaining software licenses, purchasing physical hosting resources,etc.), the usage of the service (e.g., costs for obtaining additionalstorage capacity for a highly used service), or various other factorsthat may be included in the cost for the service instances.

As such, the various factors included in the cost for the serviceinstances may be used to derive estimated costs for the serviceinstances, wherein the estimated costs may include an estimated usageper hour cost and an estimated resource cost for each service instance,which may then be multiplied to obtain an estimated total cost for eachservice instance. Additionally, in one implementation, the total costfor each service instance may include a selectable graphical controlelement. For example, in response to a selection of the total costgraphical control element, the workload management system may obtainfurther details on the underlying factors that resulted in the totalcost determination (e.g., describing costs for individual resources thatsupport the service instances, numbers of users authorized to interactor actually interacting with the service instances, etc.). As such, theservice listing scorecard may be used to create movement or retirementplans for the service instances, wherein decisions regarding whether tomove or retire the service instances may be informed through detailedinformation describing the factors underlying the cost for maintainingthe service instances. For example, moving a service instance hosted onexpensive physical resources to a virtualized data center maysubstantially reduce the cost for the service instance withoutcompromising any functionality that the service instance may provide. Inanother example, in response to determining that a first instance of aservice supports a small number of users and therefore has a large costper user, while a second instance of the service supports a large numberof users and therefore has a small cost per user, retiring the firstinstance of the service and migrating the users to the second instanceof the service may substantially reduce the overall cost for theservice.

In one implementation, the scorecards may further include an operationindex scorecard, which may be generated in an operation 430. Inparticular, FIG. 5B illustrates an exemplary instance of the operationindex scorecard that may be generated in operation 430, wherein theoperation index scorecard may be used to visualize and tune the currentoperational state in the infrastructure. In particular, the operationindex scorecard may express the overall operational state of theinfrastructure within a primary range that represents agility versusrigidness in the infrastructure, wherein whether the infrastructure hasmore agility or more rigidness may be determined from various factorssuch as security, risk, and virtualized deployment, among other things(e.g., a high degree of security may provide more rigidness while lowsecurity may provide more agility, a high degree of risk may providemore agility while low risk may provide more rigidness, a high degree ofvirtualized deployment may provide agility while a high degree ofphysical deployment may provide more rigidness, etc.). Furthermore, theoperation index scorecard may further express the overall operationalstate of the infrastructure within various secondary ranges, which mayrepresent overall complexity, cost, availability, or othercharacteristics of the current operational state for the infrastructure.

As such, in response to determining the current operational state forthe infrastructure in operation 410, the operation index scorecardgenerated in operation 420 may visually represent whether the currentoperational state has more agility or rigidness within the primaryrange, while the overall complexity, cost, and availability for thecurrent operational state may be visually represented within the varioussecondary ranges. Furthermore, in one implementation, the primary rangeand the secondary ranges may represent the current operational statewith graphical slider mechanisms, which may be selected and moved totune the current operational state. In particular, an administrator,manager, or other suitable entity may manually move the graphical slidermechanism along the primary range to broadly balance the agility and therigidness of the infrastructure to establish a desired index in theprimary range. Alternatively (or additionally), adjustments to theprimary slider mechanism may be policy-based, wherein one or morepolicies may restrict permitted movement of the primary slider withinthe primary range or automatically establish the desired index. Forexample, a particular policy may restrict how far the primary slider canbe moved towards the most agile index to prevent security risks, or theparticular policy may automatically establish the desired index toensure that the infrastructure has sufficient rigidness to prevent thesecurity risks.

In one implementation, in response to determining that the primaryslider mechanism has been moved within the primary range, the workloadmanagement system may then create a plan detailing one or more changesthat can be implemented in the infrastructure to reach the desiredindex. Furthermore, the slider mechanisms provided in the secondaryranges for complexity, cost, and availability may be automaticallyrefreshed to reflect any changes caused by moving the primary sliderwithin the primary range. As such, in response to creating the plandetailing the changes needed to reach the desired index specified by theuser or defined by any relevant policies, one or more the secondarysliders may be moved along the secondary ranges to fine-tune thecomplexity, cost, and availability of the infrastructure. For example,in one implementation, increasing the rigidness of the infrastructuremay reduce the overall complexity of the infrastructure while increasingthe overall cost and availability of the infrastructure. Thus, thesecondary sliders may provide further control for fine tuning theinfrastructure in a manner that best suits the particular needs of abusiness (e.g., in response to the primary adjustment causing anundesirable index in any of the secondary ranges, the secondary slidersmay be moved to establish a desired index in such secondary ranges).

In one implementation, in response to determining that one or more ofthe secondary sliders have been moved within the secondary ranges, theworkload management system may then create a plan detailing one or morechanges that can be implemented in the infrastructure to reach thedesired indices established in the secondary ranges. Furthermore, inresponse to the adjustment to the secondary ranges, the index in theprimary range may then be similarly refreshed to reflect any changescaused by moving the secondary sliders. Thus, the index in the primaryrange and the indices in the secondary ranges may be continuallyadjusted in an iterative manner until the desired balance betweenagility, rigidness, complexity, cost, and availability has been reached.As such, although the adjustments to the operational state of theinfrastructure has been described herein in the context of initiallytuning the primary slider in the primary range, the operational stateadjustments may proceed in any suitable order (e.g., a user may suitablyadjust the cost range first, adjust the agility versus rigidness rangenext, adjust the complexity range next, re-adjust the cost range next,etc.). In response to the establishing the desired index in the primaryrange and the desired indices in the secondary ranges, the workloadmanagement system may then finalize the plan for reaching the desiredindices and control a suitable workload to implement such changes.

In one implementation, the scorecards may further include a risk heatmap scorecard, which may be generated in an operation 440. Inparticular, FIG. 5C illustrates an exemplary instance of the risk heatmap scorecard that may be generated in operation 440, wherein the riskheat map scorecard may be used to visualize and tune risk to coverageratios in the infrastructure. In one implementation, the risk heat mapscorecard may visually display risks in different areas of theinfrastructure, wherein the risks in the different areas may be furtherrepresented across different coverage ratios for the infrastructure. Inparticular, the risk determinations displayed in the risk heat map mayrepresent risks in particular areas of the infrastructure, wherein therisk in the particular areas may vary depending on a ratio of theinfrastructure that the risk determination covers (e.g., a determinationthat the infrastructure complies with certain policy or regulatoryrequirements may be misleading or inaccurate in certain cases, such aswhere the compliance determination was based on an analysis that onlycovers ten percent or another portion of the infrastructure).

In one implementation, as shown in FIG. 5C, the risk heat map scorecardmay display risks for compliance with Sarbanes-Oxley (SOX) requirements,Payment Card Industry (PCI) standards, the Health Insurance Portabilityand Accountability Act (HIPAA), Information Technology InfrastructureLibrary (ITIL) best practices, Control Objectives for Information andRelated Technology (COBIT) requirements, or other suitable areas thatmay be associated with risk in the infrastructure. Thus, the risk heatmap scorecard may represent the risk within the various risk areas as afunction of the coverage ratio. For example, FIG. 5C visually displays alow risk of SOX non-compliance when the coverage ratio encompasses onlytwenty percent of the infrastructure, whereas the risk may be even lowerwhen the coverage ratio encompasses the entire infrastructure. Inanother example, the risk of PCI non-compliance may be high when thecoverage ratio encompasses twenty percent of the infrastructure, lowwhen the coverage ratio encompasses forty to eighty percent of theinfrastructure, but highest when the coverage ratio encompasses theentire infrastructure. Thus, the risk heat map scorecard may visuallyrepresent the risk to the infrastructure within various areas atdifferent levels of infrastructure coverage, wherein the individual riskratios in the scorecard may be selected to drill down into theunderlying parameters that resulted in the risk determination.Furthermore, in response to a selection of one or more of the individualrisk ratios in the risk heat map scorecard, the workload managementsystem may provide recommendations for improving the risk to coverageratios (e.g., identifying parameters in the infrastructure that increasethe relevant risk and recommending changes to the infrastructure tomitigate the effect that the parameters have in the particular riskarea).

In one implementation, the scorecards may further include a serviceplacement scorecard, which may be generated in an operation 450. Inparticular, FIG. 5D illustrates an exemplary instance of the serviceplacement scorecard that may be generated in operation 450, wherein theservice placement scorecard may be used to visualize and tune locationsin the infrastructure where the services, applications, workloads, orother resources may be deployed or otherwise placed. For example, theservice placement scorecard may visually represent the services,applications, and workloads running in the infrastructure in a generallysimilar manner as the service listing scorecard described in furtherdetail above. In particular, the service placement scorecard may provideidentifiers and resource names detailing the running services,applications, and workloads, which may be further indexed withparameters for security, risk, cost, and performance. In oneimplementation, the parameters may be indexed within numeric ranges(e.g., one to five) that generally represent actual measured valuesassociated with the security, risk, cost, and performance for theservices, applications, or workloads displayed in the service placementscorecard.

For example, in response determining that many users have authorizationto access or otherwise interact with a particular service but only asmall number of the authorized users actually access the service, thesecurity parameter may be assigned a high index (e.g., a large number ofauthorized users may reflect a vulnerability that can be closed becauseonly a small number of the authorized users actually access theservice). Furthermore, the index for the risk parameter may include anaggregated risk determination across different areas of theinfrastructure (e.g., derived from the risk heat map scorecard shown inFIG. 5C), the index for the cost parameter may include an aggregatedcost determination (e.g., derived from the service listing scorecardshown in FIG. 5A), and the index for the performance parameter mayreflect whether the service, application, or workload conforms to aservice level agreement that defines anticipated performance metricsversus actually measured performance metrics. The indices for thesecurity, risk, cost, and performance parameters may then be aggregatedto create a total index.

In particular, in one implementation, the total index for a particularservice, application, or workload may indicate the most effectiveplacement for the particular service, application, or workload. Inparticular, the service placement scorecard may define various rangesthat indicate whether deployment in a physical, virtualized, or clouddata center would be the most effective placement for certain services,applications, or workloads. For example, in response to defining a oneto five numeric range for the security, risk, cost, and performanceparameters, the total index for a particular service, application, orworkload may fall anywhere between four to twenty (inclusive). Thus, asshown in FIG. 5D, instances of SAP services may be recommended forplacement within a cloud data center in response to the total indexfalling in a first range (e.g., four to ten), within a virtualized datacenter in response to the total index falling in a second range (e.g.,eleven to fifteen), and within a physical data center in response to thetotal index falling in a third range (e.g., sixteen to twenty). Further,the ranges for determining whether to recommend placement within cloud,virtualized, or physical data centers may vary for different services,applications, and workloads (e.g., the cloud and virtualized deploymentranges may be larger for services that have minimal, flexible, orotherwise agile physical hosting requirements, whereas the physicaldeployment range may be larger for services that have substantial orrigid physical requirements). The recommended target for the variousservices, applications, may workloads may then be selected to viewfurther details on any factors underlying the recommended placement(e.g., the relevant ranges, factors underlying the indices for thesecurity, risk, cost, or performance parameters, etc.), and therecommended target may be selected to create a plan to move the instanceto the recommended data center.

Thus, in response to generating the service listing scorecard, theoperation index scorecard, the risk heat map scorecard, and the serviceplacement scorecard, the various scorecards may then be displayed in anoperation 460. For example, in one implementation, the variousscorecards may be displayed within one or more graphical user interfaceson any suitable display device communicatively coupled to the workloadmanagement system. As such, the administrator, manager, or other entitymay view the scorecards displayed in operation 460 to visualize theservices, applications, workloads, or other resources in theinfrastructure, and may further interact with one or more of thegraphical control elements provided in the scorecards to tune theservices, applications, workloads, or other resources in theinfrastructure. For example, FIG. 6 illustrates a flow diagram of anexemplary method 600 for tuning the information technologyinfrastructure with the service scorecards, wherein an operation 610 mayinclude displaying the service scorecards in a similar manner as notedabove with respect to operation 460 in FIG. 4.

In one implementation, an administrator, manager, or other suitableentity may then view the scorecards and interact with one or moregraphical control elements provided in the scorecards to initiate arequest to tune the infrastructure. As such, in response to theadministrator, manager, or other entity interacting with the graphicalcontrol elements in the scorecards, an operation 620 may includeanalyzing the interaction to identify characteristics of the request totune the infrastructure. For example, as described in further detailabove, the service listing scorecard may provide control elements fortuning the cost for individual services, applications, and workloads,the operation index scorecard may provide control elements for tuningthe overall agility, rigidness, complexity, cost, and availability forthe infrastructure, the risk heat map scorecard may provide controlelements for tuning risk across various areas and coverage ratios, andthe service placement scorecard may provide control elements for tuningphysical, virtualized, or cloud deployment for individual services,applications, and workloads. Thus, in response to identifying thecharacteristics of the request to tune the infrastructure, which mayinclude interaction with one or more of the scorecards, an operation 630may generate a plan to appropriately tune the infrastructure based onthe characteristics of the tuning request.

Furthermore, in response to generating the tuning plan, an operation 640may include refreshing one or more of the service scorecards to reflectchanges to the infrastructure that may be defined in the tuning plan(e.g., refreshing the service listing and/or service placementscorecards in response to a request to tune the secondary cost slider inthe operation index scorecard, refreshing the risk heat map scorecard inresponse to selecting a recommended target that moves a service from aphysical data center to a cloud data center and causes a resultingchange in the risk for the service, etc.). In one implementation, theadministrator, manager, or other entity may then view the tuning plangenerated in operation 630 and the service scorecards refreshed inoperation 640 to determine whether or not to implement the tuning plan.For example, an operation 650 may include the administrator, manager, orother entity determining that the tuning plan raises the overall costfor the infrastructure, results in increased risk, or otherwise hasundesirable consequences. Thus, in response to determining that thetuning plan should not be implemented, an operation 670 may includediscarding the infrastructure changes defined in the plan (and/orrestoring the service scorecards to states that existed prior togenerating the tuning plan). Alternatively, in response to suitablyapproving the tuning plan in operation 650, the infrastructure changesdefined in the plan may then be applied in an operation 660. Forexample, the workload management system may create and manage a tuningworkload that coordinates collaborative interaction between variousautomated and/or human entities to apply the changes defined in theplan, as described in further detail above.

Implementations of the invention may be made in hardware, firmware,software, or various combinations thereof. The invention may also beimplemented as instructions stored on a machine-readable medium, whichmay be read and executed using one or more processing devices. In oneimplementation, the machine-readable medium may include variousmechanisms for storing and/or transmitting information in a form thatcan be read by a machine (e.g., a computing device). For example, amachine-readable storage medium may include read only memory, randomaccess memory, magnetic disk storage media, optical storage media, flashmemory devices, and other media for storing information, and amachine-readable transmission media may include forms of propagatedsignals, including carrier waves, infrared signals, digital signals, andother media for transmitting information. While firmware, software,routines, or instructions may be described in the above disclosure interms of specific exemplary aspects and implementations performingcertain actions, it will be apparent that such descriptions are merelyfor the sake of convenience and that such actions in fact result fromcomputing devices, processing devices, processors, controllers, or otherdevices or machines executing the firmware, software, routines, orinstructions.

Furthermore, aspects and implementations may be described in the abovedisclosure as including particular features, structures, orcharacteristics, but it will be apparent that every aspect orimplementation may or may not necessarily include the particularfeatures, structures, or characteristics. Further, where particularfeatures, structures, or characteristics have been described inconnection with a specific aspect or implementation, it will beunderstood that such features, structures, or characteristics may beincluded with other aspects or implementations, whether or notexplicitly described. Thus, various changes and modifications may bemade to the preceding disclosure without departing from the scope orspirit of the invention, and the specification and drawings shouldtherefore be regarded as exemplary only, with the scope of the inventiondetermined solely by the appended claims.

What is claimed is:
 1. A system for providing scorecards to visualizeservices in an intelligent workload management system, comprising: anidentity vault that stores federated information defining entitlementsfor a plurality of unique identities across a plurality ofauthentication domains, the entitlements derived from single sign-onworkload identities, generated from authentication tokens that definevarious credentials and permissions assigned to any suitable user,application, system, service, or resource; a discovery engine thatdiscovers an operational state for an information technologyinfrastructure from the federated information stored in the identityvault and actual activity monitored for the plurality of uniqueidentities in the information technology infrastructure, wherein thediscovery engine is configured to: discover information that describesone or more physical resources and one or more virtualized resources inthe information technology infrastructure from the federated informationstored in the identity vault; discover information that describes one ormore services, one or more applications, and one or more workloadsrunning in the information technology infrastructure from the federatedinformation stored in the identity vault; discover dependencies thatdefine relationships between the physical resources, the virtualizedresources, the services, the applications, and the workloads running inthe information technology infrastructure from the federated informationstored in the identity vault, wherein discover further includesidentifying the relationships as: network addresses, storage locations,capacity requirements, bandwidth requirements, and life-cycle controlinformation; and discover information that describes the plurality ofunique identities access to the information technology infrastructure,wherein the discovered access information includes the entitlementsdefined in the identity vault and the actual activity monitored for theplurality of unique identities in the information technologyinfrastructure; and a display device configured to display a pluralityof scorecards that visualize the discovered physical resources, thediscovered virtualized resources, the discovered services, thediscovered applications, the discovered workloads, the discovereddependencies, and the discovered access information.
 2. The system ofclaim 1, wherein the plurality of scorecards include a service listingscorecard that describes business value, usage, and cost associated withthe discovered services, the discovered applications, and the discoveredworkloads.
 3. The system of claim 2, further comprising a managementinfrastructure configured to generate a plan to move or retire one ormore of the discovered services, the discovered applications, or thediscovered workloads identified in a request to tune the cost of theinformation technology infrastructure.
 4. The system of claim 1, whereinthe plurality of scorecards include an operation index scorecard havinga primary graphical object and a plurality of secondary graphicalobjects that visualize an overall operational state for the informationtechnology infrastructure.
 5. The system of claim 4, further comprisinga management infrastructure configured to generate a plan to tune abalance between agility and rigidness in the information technologyinfrastructure in response to a request that moves a primary slidermechanism associated with the primary graphical object within a rangedefined in the primary graphical object.
 6. The system of claim 5,wherein the management infrastructure is further configured to refreshthe plan to tune complexity, cost, or availability in the informationtechnology infrastructure in response to the request moving one or moresecondary slider mechanisms associated with one or more of the pluralityof secondary graphical object.
 7. The system of claim 1, wherein theplurality of scorecards include a risk heat map scorecard that describesrisk in one or more areas of the information technology infrastructureacross a plurality of different coverage ratios.
 8. The system of claim7, further comprising a management infrastructure configured to generatea plan to tune the risk in one or more of the areas of the informationtechnology infrastructure identified in a request that furtheridentifies one or more of the plurality of different coverage ratiosassociated with the identified area.
 9. The system of claim 1, whereinthe plurality of scorecards include a service placement scorecard thatprovides a recommended target for deploying one or more of thediscovered services, the discovered applications, or the discoveredworkloads.
 10. The system of claim 9, further comprising a managementinfrastructure configured to generate a plan to deploy one or more ofthe discovered services, the discovered applications, or the discoveredworkloads identified in a request to the recommended target, wherein therecommended target includes on of a physical data center, a virtualizeddata center, or a cloud data center.
 11. A method for providingscorecards to visualize services in an intelligent workload managementsystem, comprising: storing, in an identity vault, federated informationdefining entitlements for a plurality of unique identities across aplurality of authentication domains, the entitlements derived fromsingle sign-on workload identities, generated from authentication tokensthat define various credentials and permissions assigned to any suitableuser, application, system, service, or resource; discovering, by adiscovery engine, an operational state for an information technologyinfrastructure from the federated information stored in the identityvault and actual activity monitored for the plurality of uniqueidentities in the information technology infrastructure, whereindiscovering the operational state for the infrastructure includes:discovering, by the discovery engine, information that describes one ormore physical resources and one or more virtualized resources in theinformation technology infrastructure from the federated informationstored in the identity vault; discovering, by the discovery engine,information that describes one or more services, one or moreapplications, and one or more workloads running in the informationtechnology infrastructure from the federated information stored in theidentity vault; discovering, by the discovery engine, dependencies thatdefine relationships between the physical resources, the virtualizedresources, the services, the applications, and the workloads running inthe information technology infrastructure from the federated informationstored in the identity vault, wherein discovering further includesidentifying the relationships as: network addresses, storage locations,capacity requirements, bandwidth requirements, and life-cycle controlinformation and discovering, by the discovery engine, information thatdescribes the plurality of unique identities access to the informationtechnology infrastructure, wherein the discovered access informationincludes the entitlements defined in the identity vault and the actualactivity monitored for the plurality of unique identities in theinformation technology infrastructure; and displaying, on a displaydevice, a plurality of scorecards that visualize the discovered physicalresources, the discovered virtualized resources, the discoveredservices, the discovered applications, the discovered workloads, and thediscovered dependencies, and the discovered access information.
 12. Themethod of claim 11, wherein the plurality of scorecards include aservice listing scorecard that describes business value, usage, and costassociated with the discovered services, the discovered applications,and the discovered workloads.
 13. The method of claim 12, furthercomprising generating, by a management infrastructure, a plan to move orretire one or more of the discovered services, the discoveredapplications, or the discovered workloads identified in a request totune the cost of the information technology infrastructure.
 14. Themethod of claim 11, wherein the plurality of scorecards include anoperation index scorecard having a primary graphical object and aplurality of secondary graphical objects that visualize an overalloperational state for the information technology infrastructure.
 15. Themethod of claim 14, further comprising generating, by a managementinfrastructure, a plan to tune a balance between agility and rigidnessin the information technology infrastructure in response to a requestthat moves a primary slider mechanism associated with the primarygraphical object within a range defined in the primary graphical object.16. The method of claim 15, further comprising refreshing, by themanagement infrastructure, the plan to tune complexity, cost, oravailability in the information technology infrastructure in response tothe request moving one or more secondary slider mechanisms associatedwith one or more of the plurality of secondary graphical object.
 17. Themethod of claim 11, wherein the plurality of scorecards include a riskheat map scorecard that describes risk in one or more areas of theinformation technology infrastructure across a plurality of differentcoverage ratios.
 18. The method of claim 17, further comprisinggenerating, by a management infrastructure, a plan to tune the risk inone or more of the areas of the information technology infrastructureidentified in a request that further identifies one or more of theplurality of different coverage ratios associated with the identifiedarea.
 19. The method of claim 11, wherein the plurality of scorecardsinclude a service placement scorecard that provides a recommended targetfor deploying one or more of the discovered services, the discoveredapplications, or the discovered workloads.
 20. The method of claim 19,further comprising generating, by a management infrastructure, a plan todeploy one or more of the discovered services, the discoveredapplications, or the discovered workloads identified in a request to therecommended target, wherein the recommended target includes on of aphysical data center, a virtualized data center, or a cloud data center.